FSS-TimEx for TempEval-3: Extracting Temporal Information from Text
نویسندگان
چکیده
We describe FSS-TimEx, a module for the recognition and normalization of temporal expressions we submitted to Task A and B of the TempEval-3 challenge. FSS-TimEx was developed as part of a multilingual event extraction system, Nexus, which runs on top of the EMM news processing engine. It consists of finite-state rule cascades, using minimalistic text processing stages and simple heuristics to model the relations between events and temporal expressions. Although FSS-TimEx is already deployed within an IE application in the medical domain, we found it useful to customize its output to the TimeML standard in order to have an independent performance measure and guide further developments.
منابع مشابه
Event and Temporal Expression Extraction from Raw Text: First Step towards a Temporally Aware System
Extracting temporal information from raw text is fundamental for deep language understanding, and key to many applications like question answering, information extraction, and document summarization. Our long-term goal is to build complete temporal structure of documents and use the temporal structure in other applications like textual entailment, question answering, visualization, or others. I...
متن کاملTRIPS and TRIOS System for TempEval-2: Extracting Temporal Information from Text
Extracting temporal information from raw text is fundamental for deep language understanding, and key to many applications like question answering, information extraction, and document summarization. In this paper, we describe two systems we submitted to the TempEval 2 challenge, for extracting temporal information from raw text. The systems use a combination of deep semantic parsing, Markov Lo...
متن کاملMassively Increasing TIMEX3 Resources: A Transduction Approach
Automatic annotation of temporal expressions is a research challenge of great interest in the field of information extraction. Gold standard temporally-annotated resources are limited in size, which makes research using them difficult. Standards have also evolved over the past decade, so not all temporally annotated data is in the same format. We vastly increase available human-annotated tempor...
متن کامل05151 Summary - Annotating, Extracting and Reasoning about Time and Events
Newspaper articles and other natural-language texts describe actions, events, and states of affairs. A crucial first step toward the automatic extraction of information from these texts—for use in such applications as automatic question answering or summarization—is the capacity to identify what events are being described and to make explicit when these events occurred and which temporal relati...
متن کاملLearning Relational Structure for Temporal Relation Extraction
Recently there has been a lot of interest in using Statistical Relational Learning (SRL) models for Information Extraction (IE). One of the important IE tasks is extraction of temporal relations between events and time expressions (timex). SRL methods that use hand-written rules have been proposed for various IE tasks. In contrast, we propose an approach that employs structure learning in SRL t...
متن کامل