A semiautomatic extension of our monolingual (Spanish) TERSEO system (temporal expressions resolution system applied to event ordering) to a multilingual level is presented. TERSEO implements a method of event ordering based on temporal expression recognition and resolution. TERSEO consists of two different modules, the first module is based on a set of rules that allows the recognition of the temporal expressions in Spanish. The second module is based on a set of rules that allows the resolution of these temporal expressions (which means transforming them into a concrete date, concrete interval or fuzzy interval). Both sets of rules were defined through an empirical study of a training corpus. The extension of the system, that makes the system able to work with multilingual texts, has been made in five stages. First, a direct translation of the temporal expressions in Spanish of our knowledge database to the target language (English, Italian, French, Catalan, etc) is performed. Each expression in the target language is linked to the same resolution rule used in the source language. The second stage is a search in Google for each expression so that we eliminate all those expressions of which non exact instances are found. The third step is the obtaining of a set of keywords in the target language, that is used in the next step to look for new temporal expressions in this language, learning new rules automatically. Finally, every new rule is linked with its resolution. Besides, we present two evaluations: an evaluation of the results obtained in the extension of the system to English and an evaluation of TERSEO system in English using this automatic acquisition of new temporal expressions in which measures of precision and recall are obtained.
[1]
Gwyneth Doherty-Sneddon,et al.
The Reliability of a Dialogue Structure Coding Scheme
,
1997,
CL.
[2]
George A. Miller,et al.
WordNet: A Lexical Database for English
,
1995,
HLT.
[3]
Rafael Muñoz,et al.
TERSEO: Temporal Expression Resolution System Applied to Event Ordering
,
2003,
TSD.
[4]
Janyce Wiebe,et al.
An Empirical Approach to Temporal Reference Resolution
,
1997,
EMNLP.
[5]
Robert Gaizauskas,et al.
On the Importance of Annotating Event-Event Temporal Relations in Text
,
2022
.
[6]
Fernando Llopis,et al.
Cross-Language Experiments with IR-n System
,
2003,
CLEF.
[7]
Bernice W. Polemis.
Nonparametric Statistics for the Behavioral Sciences
,
1959
.