While there is a wide consensus in the NLP community over the modeling of temporal relations between events, mainly based on Allen’s temporal logic, the question on how to annotate other types of event relations, in particular causal ones, is still open. In this work, we present some annotation guidelines to capture causality between event pairs, partly inspired by TimeML. We then implement a rule-based algorithm to automatically identify explicit causal relations in the TempEval-3 corpus. Based on this annotation, we report some statistics on the behavior of causal cues in text and perform a preliminary investigation on the interaction between causal and temporal relations.

Mirza, P., Sprugnoli, R., Tonelli, S., Speranza, M., Annotating Causality in the TempEval-3 Corpus, Paper, in Proceedings of the EACL 2014 Workshop on Computational Approaches to Causality in Language (CAtoCL), (Gothenburg, SWEDEN, 26-26 April 2014), Association for Computational Linguistics, Gothenburg, SWEDEN 2014: 10-19 [http://hdl.handle.net/10807/132951]

Annotating Causality in the TempEval-3 Corpus

Sprugnoli, Rachele;
2014

Abstract

While there is a wide consensus in the NLP community over the modeling of temporal relations between events, mainly based on Allen’s temporal logic, the question on how to annotate other types of event relations, in particular causal ones, is still open. In this work, we present some annotation guidelines to capture causality between event pairs, partly inspired by TimeML. We then implement a rule-based algorithm to automatically identify explicit causal relations in the TempEval-3 corpus. Based on this annotation, we report some statistics on the behavior of causal cues in text and perform a preliminary investigation on the interaction between causal and temporal relations.
2014
Inglese
Proceedings of the EACL 2014 Workshop on Computational Approaches to Causality in Language (CAtoCL)
EACL 2014 Workshop on Computational Approaches to Causality in Language (CAtoCL)
Gothenburg, SWEDEN
Paper
26-apr-2014
26-apr-2014
9781937284862
Association for Computational Linguistics
Mirza, P., Sprugnoli, R., Tonelli, S., Speranza, M., Annotating Causality in the TempEval-3 Corpus, Paper, in Proceedings of the EACL 2014 Workshop on Computational Approaches to Causality in Language (CAtoCL), (Gothenburg, SWEDEN, 26-26 April 2014), Association for Computational Linguistics, Gothenburg, SWEDEN 2014: 10-19 [http://hdl.handle.net/10807/132951]
File in questo prodotto:
File Dimensione Formato  
W14-0702.pdf

accesso aperto

Tipologia file ?: Versione Editoriale (PDF)
Licenza: Creative commons
Dimensione 157.75 kB
Formato Adobe PDF
157.75 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10807/132951
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact