Supervised approach to recognise Polish temporal expressions and rule-based interpretation of timexes

Abstract

A key challenge of the Information Extraction in Natural Language Processing is the ability to recognise and classify temporal expressions (timexes). It is a crucial source of information about when something happens, how often something occurs or how long something lasts. Timexes extracted automatically from text, play a major role in many Information Extraction systems, such as question answering or event recognition. We prepared a broad specification of Polish timexes – PLIMEX. It is based on the state-of-the-art annotation guidelines for English, mainly TIMEX2 and TIMEX3 (a part of TimeML – Markup Language for Temporal and Event Expressions). We have expanded our specification for a description of the local meaning of timexes, based on LTIMEX annotation guidelines for English. Temporal description supports further event identification and extends event description model, focussing on anchoring events in time, events ordering and reasoning about the persistence of events. We prepared the specification, which is designed to address these issues, and we annotated all documents in Polish Corpus of Wroclaw University of Technology (KPWr) using our annotation guidelines. We also adapted our Liner2 machine learning system to recognise Polish timexes and we propose two-phase method to select a subset of features for Conditional Random Fields sequence labelling method. This article presents the whole process of corpus annotation, evaluation of inter-annotator agreement, extending Liner2 system with new features and evaluation of the recognition models before and after feature selection with the analysis of statistical significance of differences. Liner2 with presented models is available as open source software under the GNU General Public License.

Improved Recognition and Normalisation of Polish Temporal Expressions

“…All English translations of Polish examples are given in parentheses. These examples are presented in (Kocoń and Marcińczuk, 2017), and a broad description of each timex type is presented in .…”

“…calendar date (YYYY-MM-DD), week of the year (YYYY-Wxx), hour (hh:mm:ss), date & hour (YYYY-MM-DDThh:mm:ss), duration (PxW). Table 1 shows example values of the VAL attribute and the semantic meaning (Kocoń and Marcińczuk, 2017 Normalisation in the TimeML standard involves the determination of the global semantics for a timex. There is no indirect form of notation of the local semantics.…”

“…HeidelTime 4 , )), which often use their own intermediate standard of normalisation. For that purpose LTIMEX standard was adapted (Kocoń and Marcińczuk, 2017). It can be used to determine the local semantics of timexes.…”

“…If the temporal expression is explicit, there is no difference between LVAL and VAL representation. The specification is fully described in work (Kocoń and Marcińczuk, 2017). Table 2 shows the example values of the LVAL attribute and the semantic meaning.…”

Liner2 — a Generic Framework for Named Entity Recognition

“…It provides a set of modules (based on statistical models, dictionaries, rules and heuristics) which recognize and annotate certain types of phrases. The framework was already used for recognition of named entities (different levels of granularity, including boundaries, coarse-and fine-grained categories) (Marcińczuk et al, 2012), temporal expressions (Kocoń and Marcińczuk, 2016b) and event mentions (Kocoń and Marcińczuk, 2016a) for Polish. Figure 1: Precision (P), recall (R) and F-measure (F) for various task obtained with Liner2.…”