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Tense and Temporal Relations in Italian Text/Discourse.

                                         Tommaso Caselli
                                          ILC-CNR, Pisa
                                  tommaso.caselli@ilc.cnr.it

0.
Aim of the work: Revision of tense interpretation in text/discourse (tense as a discourse anaphor)
                 Temporal relations between eventualities in adjacent sentences
                 Role of the tense in recovering temporal relations

1.
Assumptions: tense semantics is analyzed in terms of a neo-reichenbachian approach

2 distinctions: BASIC TEMPORAL MEANING OF TENSE
                 TENSE MEANING IN TEXTUAL DOMAIN(Smith 2004)  text/discourse
      •   E = moment of event
      •   S = moment of speech (deictic centre)
      •   Rpt = representational device. It corresponds to the original Reichenbachian notion of
          moment of reference. It is responsible for the signalling that tense IS REFERENTIAL.
          Rpt is always simultaneous with E
      •   R = second deictic centre. Required only by some tense forms; e.g. Trapassato I (Past
          Perfect); Futuro Composto (Future Perfect) ( Comrie, 1985)

           Tense Forms                                           Absolute Meaning
           Present (Present)                                     (E = S) / (Rpt = E)
           Passato Semplice (Simple Past); Imperfetto            (E < S) / (Rpt = E)
           (Imperfait); Passato Composto (Present Perfect
           + Simple Past)
           Trapassato I & II (Past Perfect)                      (E < R) • (R < S) / (Rpt = E)
           Futuro Semplice (Future)                              (E > S) / (Rpt = E)
           Futuro Composto (Future Perfect)                      (E < R) • (R > S) / (Rpt = E)
           Futuro nel Passato (Future-in-the-Past)               (E > R) • (R < S) / (Rpt = E)
                           Table 1 – Representation of the absolute tense meanings.
1.1

Temporal relations: they are INFERENTIAL PROCESSES which are activated on the basis of
semantic and pragmatic principles.

Temporal relations are the result of the combination of linguistic and contextual (extra-linguistic)
information which starts from a relevant input and contribute to determine the informational
content of an utterance or a sentence. They are explicatures and not implicatures (Sperber-Wilson,
2004).

Temporal relations cannot be considered as a by-product of the computation of discourse
structure (Lascarides-Asher, 1993).

                                                                                                       1
CHRONOS 2009 - 9th International Conference on Tense, Aspect and Modality. Paris, September 2-4 2009
1.2
Tense in text/discourse: sequences of adjacent sentences.

Tense appears as the primary source of information we have at disposal when identifying the
temporal relations between two eventualities.

To account for the interpretation of tensed clauses or sentences in text/discourse we need a further
point:

    •   A: temporal textual anchor.
            o The presence of A introduces two further relations:
               (Rpt relative to A): textual interpretation of tense
               (A relative to S): it expresses the relation between the specific referred time where
               the eventuality occurs and the S.

   Tense Forms                                                    Tense meaning in text/discourse
   Present (Present)                                              (E = S) / (Rpt = E) / (Rpt = A) /
                                                                  (A = S)
   Passato Semplice (Simple Past); Passato Composto               (E < S) / (Rpt = E) / (Rpt < A) /
   (Present Perfect + Simple Past)                                (A < S)
   Imperfetto (Imparfait)                                         (E < S) / (Rpt = E) / (Rpt = A) /
                                                                  (A < S)
   Trapassato I & II (Past Perfect)                               (E < R) • (R < S) / (Rpt = E) /
                                                                  [(Rpt < A) / (R = A)] / (A < S)
   Futuro Semplice (Future)                                       (E > S) / (Rpt = E) / (Rpt > A) /
                                                                  (A > S)
   Futuro Composto (Future Perfect)                               (E < R) • (R > S) / (Rpt = E) /
                                                                  [(Rpt < A) / (R = A)] / (A > S)
   Futuro nel Passato (Future-in-the-Past)                        (E > R) • (R < S) / (Rpt = E) /
                                                                  [(Rpt > A) / (R = A)] / (A < S)
                  Table 2 – Representation of tense meaning in the text/discourse dimension.

A is a PARAMETER.

    a) Marco è caduto{passato composto}. Giovanni lo ha spinto{passato composto}.
       Marco fell. Giovanni pushed him.
       [(E1 < S) / (Rpt1 = E1 ) / (Rpt1 < A1) / (Rpt1 < S)] / [(E2 < S) / (Rpt2 = E2 ) /
       (Rpt2 < A2 ) / (Rpt2 < S)]

    b) Marco è caduto{passato composto}. Giovanni lo aveva spinto{trapassato I}.
       Marco fell. Giovanni had pushed him.
       [(E1 < S) / (Rpt1 = E1 ) / (Rpt1 < A1) / (Rpt1 < S)] / [((E2 < R2 ) • (R2 < S)) /
       (Rpt2 = E2 ) / (Rpt2 < A2 ) / (R2 = A2 ) / (Rpt2 < S)]

 the setting of the A is varied and in particular: i.) the first tensed eventuality always assigns the A
the default value, i.e. S ; ii.) subsequent tensed eventualities may assign the A either the default
value (like in a)) or the moment of reference of the preceding tensed eventualities, Rpt i-1 (like in b)).


                                                                                                         2
CHRONOS 2009 - 9th International Conference on Tense, Aspect and Modality. Paris, September 2-4 2009
Questions:

    1.    How to set the A in a principled way?
    2.    What is the role of tense for recovering temporal relations between eventualities in a
         text/discourse? Is tense responsible for the ordering of the eventualities both in a) and in b)?

2.
Empirical data

2 experiments on 34 Italian subjects.
    - Experiment 1: 28 subjects (none of them with knowledge in Linguistics); 52 couples of
       sentences (33 automatically extracted from a corpus + 19 manually modified). Highly
       controlled situation.
    -    Experiment 2: 6 subjects (student in Linguistics); 33 couples of sentences extracted from the
         corpus – no manual modification.
Tasks:
    -    identify the temporal relation between two selected (verbal) eventualities; 5 temporal
         relations available: BEFORE, AFTER, SIMULTANEOUS, OVERLAP; NO RELATION;
    -    identify the source of information which has been felt as the most salient, i.e. responsible for
         the identification of the temporal relation; different granularity according to the subjects’
         background (Experiment 1: TENSE, TEMPORAL EXPRESSIONS, NOT SPECIFIED;
         Experiment 2: TENSE, SIGNAL, VIEWPOINT, SEMANTICS, TEMPORAL EXPRESSIONS,
         NOT SPECIFIED).
2.1. Results

 the identification of a temporal relation between two consecutive eventualities IS NOT an easy
task.

Agreement of the annotators ranges between 0.49 < K < 0.581
 the agreement increases (K = 0.65) the more coarse grained is the set of temporal relations
(conceptual neighbours; Freska 1992)

Absolute Same Tense sequences: sequences of adjacent eventualities where the tenses, meaning and
superficial form, are exactly the same.
Smooth Tense Shift sequences: sequences of the kind Passato Composto – Imperfetto (Imperfait).
Same tense meaning but different surface form.
Tense Shift sequences: sequences of adjacent eventualities where the tenses, meaning and
superficial form, are different.




1
 K is the symbol for the Kappa coefficient. It is considered a more robust measure than simple percent
agreement calculation since it takes into account the agreement occurring by chance.
                                                                                                        3
CHRONOS 2009 - 9th International Conference on Tense, Aspect and Modality. Paris, September 2-4 2009
Table 3- Results from Experiment 1 for the sources of information




                      Table 4 - Results from Experiment 2 for the sources of information

                                                                                                       4
CHRONOS 2009 - 9th International Conference on Tense, Aspect and Modality. Paris, September 2-4 2009
On the basis of the analysis of the data from the experiments we argue that:

 tense is a primary source of information for the identification of temporal relations between
adjacent eventualities BUT it is NOT the most salient
 tense is a necessary and sufficient information for ordering eventualities (identify a UNIQUE
temporal relation value) only in presence of tense shifts, i.e. different configuration of the E, R, S,
moments/points.
 shift in tense is the only “condition” which offers a principled way to set the A in subsequent
sentences, in particular:
                       • sequences of same tense always set A = S
                       • sequences with tense shift set A = Rpt i-1
thus:

      a) Marco è caduto{passato composto}. Giovanni lo ha spinto{passato composto}.
         Marco fell. Giovanni pushed him.
         [(E1 < S) / (Rpt1 = E1 ) / (Rpt1 < S)] / [(E2 < S) / (Rpt2 = E2 ) / (Rpt2 < S) 
      underspecified temporal relation
      b) Marco è caduto{passato composto}. Giovanni lo aveva spinto{trapassato I}.
         Marco fell. Giovanni had pushed him.
         [(E1 < S) / (Rpt1 = E1 ) / (Rpt1 < S)] / [((E2 < R2 ) • (R2 < E2 ) / (Rpt2 < Rpt1 ) / (R2 =
         Rpt1)]  E2 before E1

2.2.

Speculations on the Imperfetto (Imperfait)

 the analysis of the data suggests that the Imperfetto could provide a setting for the A in
sequences of the kind Passato Composto (Simple Past + Present Perfect) – Imperfetto (Imperfait),
namely: A = Rpt i-1 where (Rpt = A), although such sequences qualifies as same tense sequences as
far as the configuration of the basic moments is concerned.
 the Imperfetto (Imperfait) in its standard interpretation = constraint for the validity of this
statement
 N.B. influence of Aspect – viewpoint (see data for Smooth Tense shift in Table 4)
 the temporal relation which can be inferred in this case is not unique but it is a coarse grained
relations which can be labeled as CONTEMPORARY (it includes overlap , is_finished, is_during,
is_started, simultaneous, starts, during, is_overlap; see Freska, 1992; Allen, 1983)

3.0

Advantages with respect to previous approaches:
 the role of tense in temporal relations has been clarified;
 overcoming of the limitations of traditional temporal anaphora approaches, in particular with
respect to the role of the Rpt, R. (Hinrichs, 1986; Partee, 1984; Webber, 1988)
 sequences of Trapassato I (past perfect) are treated in an uniform way with respect to other same
tense sequences
 the presence of the A is not innovative per sé (see Bertinetto, 1986). This work has provided a
systematic method to use it and of its contribution for the computation of temporal relations
                                                                                                  5
CHRONOS 2009 - 9th International Conference on Tense, Aspect and Modality. Paris, September 2-4 2009
 no need to state the presence of a particular discourse mode (Smith, 2004) in order to specify the
anaphoric properties of tense
 tense is anaphoric, in particular tense is a discourse anaphor (Webber, 1988). Its anaphoric
behaviour is similar to that of definite NPs BUT a special kind, namely bridging definite NPs:

•   Bridging definites have their own referential •         Tense has its own referential property,
    properties like a definite NP                           represented by the Rpt
•   Bridging NPs give rise to an indirect •                 Sequence   of  tenses   tend   to  refer  indirectly 
    anaphoric link to a previously mentioned                one  to the  other  so that  to  create  multiple 
    entity                                                  bridges.   Sequences   of   eventualities   at   the 
                                                            same tense, which do not allow a principled 
                                                            assignment   of   the   A   parameter,   identify   a 
                                                            general   temporal   focus,   since   all   their 
                                                            reference points, Rpts, are collocated in the 
                                                            same   temporal   dimension   providing   a 
                                                            continuation of the general temporal focus. 
                                                            On   the   contrary,   in   presence   of   shifts   in 
                                                            tense,   the   temporal   focus   of   the   two 
                                                            eventualities  differs. Their Rpts are
                                                            collocated in two different dimensions

References

Allen, J. (1983). Maintainig knowledge about temporal intervals. Communications of ACM, 26(11),
832:43.
Bertinetto, P. (1986). Tempo, Aspetto e Azione nel verbo Italiano. Il sistema dell’indicativo.
Accademia della Crusca, Firenze.
Blackburn, P. (1994). Tense, temporal reference and tense logic. Journal of Semantics, 11(1-2),
83:101.
Blackburn, P. & Lascarides, A. (1992). Sorts and operators for temporal semantics. In Proceedings
of the Fourth Symposium on Logic and Language.
Bonomi, A. & Zucchi, A. (2001). Tempo e linguaggio: introduzione alla semantica del tempo e
dell'aspetto verbale. B. Mondadori.
Carletta, J. (1996). Assessing agreement on classification tasks: The kappa statistic. Computational
Linguistics, 22, 249:54.
Caselli, T. 2009. Basi cognitive per l'ordinamento temporale degli eventi. In Atti CODISCO 2008
Casellit, T. 2009. Time, Events and Temporal Relations: an Empirical Model for Temporal
Processing of Italian Texts. Ph.D. Dissertation, University of Pisa, available at
http://etd.adm.unipi.it/theses/available/etd­04242009­113147/
Comrie, B. (1985). Tense. CUP, Cambridge.
De Mulder, W. (2004). Can there be a non temporal definition of the French imparfait. In F.
Brisard, editor, Language and revolution / Language and time, Universiteit Antwerpen, 195:222.
De Mulder, W. & Vetters, C. (2002). The French imparfait, determiners and grounding.
In F. Brisard, editor, Grounding, Mouton de Gruyter, Berlin, 113: 149.
Dowty, D. (1986). The effects of aspectual class on the temporal structure of discourse: Semantics
or pragmatics? Linguistics and Philosophy, 9, 37:61.
Freska, C. (1992). Temporal reasoning based on semi-intervals. Artifcial Intelligence, 54, 199:227.
Hinrichs, E. (1986). Temporal anaphora in discourses of English. Linguistics and philosophy, 9(1),
                                                                                                    6
CHRONOS 2009 - 9th International Conference on Tense, Aspect and Modality. Paris, September 2-4 2009
63:82.
Hobbs, J. R. & Pustejovsky, J. (2003). Annotating and reasoning about time and events. In
Proceedings of the American Association for Artificial Intellingence Spring Symposium
on Logical Formalization of Commonsense Reasoning (AAAI-03).
ISO, S. W. G. (2008). ISO DIS 24617-1: 2008 Language resource management - Semantic
annotation framework - Part 1: Time and events. ISO Central Secretariat, Geneva.
Kamp, H. & Reyle, U. (1993). From Discourse to Logic. Introduction to the Modeltheoretic
Semantics of Natural Language, Formal Logic and Discourse representation Theory. Kluwer.
Kehler, A. (2000). Resolving temporal relations using tense meaning and discourse interpretation.
In M. Faller, S. Kaufmann, and M. Pauly, editors, Formalizing the dynamics of information. CSLI
Publications, 189:207
Mani, I. (2007). Chronoscopes: A theory of underspecified temporal representation. In F. Schilder,
G. Katz, and J. Pustejovsky, editors, Annotating, Extracting and Reasoning about Time and Events,
LNAI. Springer-Verlag, Berlin Heidelberg, 127:139
Mani, I. & Pustejovsky, J. (2001). Temporal discourse models for narrative structure. In
Proceedings of the ACL Workshop on Spatial and Temporal Information Processing (ACL-01).
Partee, H. (1984). Nominal and temporal anaphora. Linguistics and philosophy, 7, 243:86.
Smith, C. (2003). Modes of Discourse: the local structure of texts. CUP, Cambridge.
Smith, C. (2004). The domain of tense. In J. Gu_eron and J. Lecarme, editors, The Syntax
of Time. MIT.
Smith, C. (2006). The pragmatics and semantics of temporal meaning. In P. Denis, E. McCready,
A. Palmer, and B. Reese, editors, Proceedings of the Texas Linguistic Forum 2004. Cascadilla
Press.
Webber, B. (1988). Tense as discourse anaphor. Computational Linguistics, 14(2), 61:73.




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CHRONOS 2009 - 9th International Conference on Tense, Aspect and Modality. Paris, September 2-4 2009

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Tense and temporal Relations in Italian Text/Discourse

  • 1. Tense and Temporal Relations in Italian Text/Discourse. Tommaso Caselli ILC-CNR, Pisa tommaso.caselli@ilc.cnr.it 0. Aim of the work: Revision of tense interpretation in text/discourse (tense as a discourse anaphor) Temporal relations between eventualities in adjacent sentences Role of the tense in recovering temporal relations 1. Assumptions: tense semantics is analyzed in terms of a neo-reichenbachian approach 2 distinctions: BASIC TEMPORAL MEANING OF TENSE TENSE MEANING IN TEXTUAL DOMAIN(Smith 2004)  text/discourse • E = moment of event • S = moment of speech (deictic centre) • Rpt = representational device. It corresponds to the original Reichenbachian notion of moment of reference. It is responsible for the signalling that tense IS REFERENTIAL. Rpt is always simultaneous with E • R = second deictic centre. Required only by some tense forms; e.g. Trapassato I (Past Perfect); Futuro Composto (Future Perfect) ( Comrie, 1985) Tense Forms Absolute Meaning Present (Present) (E = S) / (Rpt = E) Passato Semplice (Simple Past); Imperfetto (E < S) / (Rpt = E) (Imperfait); Passato Composto (Present Perfect + Simple Past) Trapassato I & II (Past Perfect) (E < R) • (R < S) / (Rpt = E) Futuro Semplice (Future) (E > S) / (Rpt = E) Futuro Composto (Future Perfect) (E < R) • (R > S) / (Rpt = E) Futuro nel Passato (Future-in-the-Past) (E > R) • (R < S) / (Rpt = E) Table 1 – Representation of the absolute tense meanings. 1.1 Temporal relations: they are INFERENTIAL PROCESSES which are activated on the basis of semantic and pragmatic principles. Temporal relations are the result of the combination of linguistic and contextual (extra-linguistic) information which starts from a relevant input and contribute to determine the informational content of an utterance or a sentence. They are explicatures and not implicatures (Sperber-Wilson, 2004). Temporal relations cannot be considered as a by-product of the computation of discourse structure (Lascarides-Asher, 1993). 1 CHRONOS 2009 - 9th International Conference on Tense, Aspect and Modality. Paris, September 2-4 2009
  • 2. 1.2 Tense in text/discourse: sequences of adjacent sentences. Tense appears as the primary source of information we have at disposal when identifying the temporal relations between two eventualities. To account for the interpretation of tensed clauses or sentences in text/discourse we need a further point: • A: temporal textual anchor. o The presence of A introduces two further relations: (Rpt relative to A): textual interpretation of tense (A relative to S): it expresses the relation between the specific referred time where the eventuality occurs and the S. Tense Forms Tense meaning in text/discourse Present (Present) (E = S) / (Rpt = E) / (Rpt = A) / (A = S) Passato Semplice (Simple Past); Passato Composto (E < S) / (Rpt = E) / (Rpt < A) / (Present Perfect + Simple Past) (A < S) Imperfetto (Imparfait) (E < S) / (Rpt = E) / (Rpt = A) / (A < S) Trapassato I & II (Past Perfect) (E < R) • (R < S) / (Rpt = E) / [(Rpt < A) / (R = A)] / (A < S) Futuro Semplice (Future) (E > S) / (Rpt = E) / (Rpt > A) / (A > S) Futuro Composto (Future Perfect) (E < R) • (R > S) / (Rpt = E) / [(Rpt < A) / (R = A)] / (A > S) Futuro nel Passato (Future-in-the-Past) (E > R) • (R < S) / (Rpt = E) / [(Rpt > A) / (R = A)] / (A < S) Table 2 – Representation of tense meaning in the text/discourse dimension. A is a PARAMETER. a) Marco è caduto{passato composto}. Giovanni lo ha spinto{passato composto}. Marco fell. Giovanni pushed him. [(E1 < S) / (Rpt1 = E1 ) / (Rpt1 < A1) / (Rpt1 < S)] / [(E2 < S) / (Rpt2 = E2 ) / (Rpt2 < A2 ) / (Rpt2 < S)] b) Marco è caduto{passato composto}. Giovanni lo aveva spinto{trapassato I}. Marco fell. Giovanni had pushed him. [(E1 < S) / (Rpt1 = E1 ) / (Rpt1 < A1) / (Rpt1 < S)] / [((E2 < R2 ) • (R2 < S)) / (Rpt2 = E2 ) / (Rpt2 < A2 ) / (R2 = A2 ) / (Rpt2 < S)]  the setting of the A is varied and in particular: i.) the first tensed eventuality always assigns the A the default value, i.e. S ; ii.) subsequent tensed eventualities may assign the A either the default value (like in a)) or the moment of reference of the preceding tensed eventualities, Rpt i-1 (like in b)). 2 CHRONOS 2009 - 9th International Conference on Tense, Aspect and Modality. Paris, September 2-4 2009
  • 3. Questions: 1. How to set the A in a principled way? 2. What is the role of tense for recovering temporal relations between eventualities in a text/discourse? Is tense responsible for the ordering of the eventualities both in a) and in b)? 2. Empirical data 2 experiments on 34 Italian subjects. - Experiment 1: 28 subjects (none of them with knowledge in Linguistics); 52 couples of sentences (33 automatically extracted from a corpus + 19 manually modified). Highly controlled situation. - Experiment 2: 6 subjects (student in Linguistics); 33 couples of sentences extracted from the corpus – no manual modification. Tasks: - identify the temporal relation between two selected (verbal) eventualities; 5 temporal relations available: BEFORE, AFTER, SIMULTANEOUS, OVERLAP; NO RELATION; - identify the source of information which has been felt as the most salient, i.e. responsible for the identification of the temporal relation; different granularity according to the subjects’ background (Experiment 1: TENSE, TEMPORAL EXPRESSIONS, NOT SPECIFIED; Experiment 2: TENSE, SIGNAL, VIEWPOINT, SEMANTICS, TEMPORAL EXPRESSIONS, NOT SPECIFIED). 2.1. Results  the identification of a temporal relation between two consecutive eventualities IS NOT an easy task. Agreement of the annotators ranges between 0.49 < K < 0.581  the agreement increases (K = 0.65) the more coarse grained is the set of temporal relations (conceptual neighbours; Freska 1992) Absolute Same Tense sequences: sequences of adjacent eventualities where the tenses, meaning and superficial form, are exactly the same. Smooth Tense Shift sequences: sequences of the kind Passato Composto – Imperfetto (Imperfait). Same tense meaning but different surface form. Tense Shift sequences: sequences of adjacent eventualities where the tenses, meaning and superficial form, are different. 1 K is the symbol for the Kappa coefficient. It is considered a more robust measure than simple percent agreement calculation since it takes into account the agreement occurring by chance. 3 CHRONOS 2009 - 9th International Conference on Tense, Aspect and Modality. Paris, September 2-4 2009
  • 4. Table 3- Results from Experiment 1 for the sources of information Table 4 - Results from Experiment 2 for the sources of information 4 CHRONOS 2009 - 9th International Conference on Tense, Aspect and Modality. Paris, September 2-4 2009
  • 5. On the basis of the analysis of the data from the experiments we argue that:  tense is a primary source of information for the identification of temporal relations between adjacent eventualities BUT it is NOT the most salient  tense is a necessary and sufficient information for ordering eventualities (identify a UNIQUE temporal relation value) only in presence of tense shifts, i.e. different configuration of the E, R, S, moments/points.  shift in tense is the only “condition” which offers a principled way to set the A in subsequent sentences, in particular: • sequences of same tense always set A = S • sequences with tense shift set A = Rpt i-1 thus: a) Marco è caduto{passato composto}. Giovanni lo ha spinto{passato composto}. Marco fell. Giovanni pushed him. [(E1 < S) / (Rpt1 = E1 ) / (Rpt1 < S)] / [(E2 < S) / (Rpt2 = E2 ) / (Rpt2 < S)  underspecified temporal relation b) Marco è caduto{passato composto}. Giovanni lo aveva spinto{trapassato I}. Marco fell. Giovanni had pushed him. [(E1 < S) / (Rpt1 = E1 ) / (Rpt1 < S)] / [((E2 < R2 ) • (R2 < E2 ) / (Rpt2 < Rpt1 ) / (R2 = Rpt1)]  E2 before E1 2.2. Speculations on the Imperfetto (Imperfait)  the analysis of the data suggests that the Imperfetto could provide a setting for the A in sequences of the kind Passato Composto (Simple Past + Present Perfect) – Imperfetto (Imperfait), namely: A = Rpt i-1 where (Rpt = A), although such sequences qualifies as same tense sequences as far as the configuration of the basic moments is concerned.  the Imperfetto (Imperfait) in its standard interpretation = constraint for the validity of this statement  N.B. influence of Aspect – viewpoint (see data for Smooth Tense shift in Table 4)  the temporal relation which can be inferred in this case is not unique but it is a coarse grained relations which can be labeled as CONTEMPORARY (it includes overlap , is_finished, is_during, is_started, simultaneous, starts, during, is_overlap; see Freska, 1992; Allen, 1983) 3.0 Advantages with respect to previous approaches:  the role of tense in temporal relations has been clarified;  overcoming of the limitations of traditional temporal anaphora approaches, in particular with respect to the role of the Rpt, R. (Hinrichs, 1986; Partee, 1984; Webber, 1988)  sequences of Trapassato I (past perfect) are treated in an uniform way with respect to other same tense sequences  the presence of the A is not innovative per sé (see Bertinetto, 1986). This work has provided a systematic method to use it and of its contribution for the computation of temporal relations 5 CHRONOS 2009 - 9th International Conference on Tense, Aspect and Modality. Paris, September 2-4 2009
  • 6.  no need to state the presence of a particular discourse mode (Smith, 2004) in order to specify the anaphoric properties of tense  tense is anaphoric, in particular tense is a discourse anaphor (Webber, 1988). Its anaphoric behaviour is similar to that of definite NPs BUT a special kind, namely bridging definite NPs: • Bridging definites have their own referential • Tense has its own referential property, properties like a definite NP represented by the Rpt • Bridging NPs give rise to an indirect • Sequence   of  tenses   tend   to  refer  indirectly  anaphoric link to a previously mentioned one  to the  other  so that  to  create  multiple  entity bridges.   Sequences   of   eventualities   at   the  same tense, which do not allow a principled  assignment   of   the   A   parameter,   identify   a  general   temporal   focus,   since   all   their  reference points, Rpts, are collocated in the  same   temporal   dimension   providing   a  continuation of the general temporal focus.  On   the   contrary,   in   presence   of   shifts   in  tense,   the   temporal   focus   of   the   two  eventualities  differs. Their Rpts are collocated in two different dimensions References Allen, J. (1983). Maintainig knowledge about temporal intervals. Communications of ACM, 26(11), 832:43. Bertinetto, P. (1986). Tempo, Aspetto e Azione nel verbo Italiano. Il sistema dell’indicativo. Accademia della Crusca, Firenze. Blackburn, P. (1994). Tense, temporal reference and tense logic. Journal of Semantics, 11(1-2), 83:101. Blackburn, P. & Lascarides, A. (1992). Sorts and operators for temporal semantics. In Proceedings of the Fourth Symposium on Logic and Language. Bonomi, A. & Zucchi, A. (2001). Tempo e linguaggio: introduzione alla semantica del tempo e dell'aspetto verbale. B. Mondadori. Carletta, J. (1996). Assessing agreement on classification tasks: The kappa statistic. Computational Linguistics, 22, 249:54. Caselli, T. 2009. Basi cognitive per l'ordinamento temporale degli eventi. In Atti CODISCO 2008 Casellit, T. 2009. Time, Events and Temporal Relations: an Empirical Model for Temporal Processing of Italian Texts. Ph.D. Dissertation, University of Pisa, available at http://etd.adm.unipi.it/theses/available/etd­04242009­113147/ Comrie, B. (1985). Tense. CUP, Cambridge. De Mulder, W. (2004). Can there be a non temporal definition of the French imparfait. In F. Brisard, editor, Language and revolution / Language and time, Universiteit Antwerpen, 195:222. De Mulder, W. & Vetters, C. (2002). The French imparfait, determiners and grounding. In F. Brisard, editor, Grounding, Mouton de Gruyter, Berlin, 113: 149. Dowty, D. (1986). The effects of aspectual class on the temporal structure of discourse: Semantics or pragmatics? Linguistics and Philosophy, 9, 37:61. Freska, C. (1992). Temporal reasoning based on semi-intervals. Artifcial Intelligence, 54, 199:227. Hinrichs, E. (1986). Temporal anaphora in discourses of English. Linguistics and philosophy, 9(1), 6 CHRONOS 2009 - 9th International Conference on Tense, Aspect and Modality. Paris, September 2-4 2009
  • 7. 63:82. Hobbs, J. R. & Pustejovsky, J. (2003). Annotating and reasoning about time and events. In Proceedings of the American Association for Artificial Intellingence Spring Symposium on Logical Formalization of Commonsense Reasoning (AAAI-03). ISO, S. W. G. (2008). ISO DIS 24617-1: 2008 Language resource management - Semantic annotation framework - Part 1: Time and events. ISO Central Secretariat, Geneva. Kamp, H. & Reyle, U. (1993). From Discourse to Logic. Introduction to the Modeltheoretic Semantics of Natural Language, Formal Logic and Discourse representation Theory. Kluwer. Kehler, A. (2000). Resolving temporal relations using tense meaning and discourse interpretation. In M. Faller, S. Kaufmann, and M. Pauly, editors, Formalizing the dynamics of information. CSLI Publications, 189:207 Mani, I. (2007). Chronoscopes: A theory of underspecified temporal representation. In F. Schilder, G. Katz, and J. Pustejovsky, editors, Annotating, Extracting and Reasoning about Time and Events, LNAI. Springer-Verlag, Berlin Heidelberg, 127:139 Mani, I. & Pustejovsky, J. (2001). Temporal discourse models for narrative structure. In Proceedings of the ACL Workshop on Spatial and Temporal Information Processing (ACL-01). Partee, H. (1984). Nominal and temporal anaphora. Linguistics and philosophy, 7, 243:86. Smith, C. (2003). Modes of Discourse: the local structure of texts. CUP, Cambridge. Smith, C. (2004). The domain of tense. In J. Gu_eron and J. Lecarme, editors, The Syntax of Time. MIT. Smith, C. (2006). The pragmatics and semantics of temporal meaning. In P. Denis, E. McCready, A. Palmer, and B. Reese, editors, Proceedings of the Texas Linguistic Forum 2004. Cascadilla Press. Webber, B. (1988). Tense as discourse anaphor. Computational Linguistics, 14(2), 61:73. 7 CHRONOS 2009 - 9th International Conference on Tense, Aspect and Modality. Paris, September 2-4 2009