Marcel Cori

Semantics of calendar adverbials for information retrieval

Unlike most approaches in the field of temporal expressions annotation, we consider that temporal adverbials could be relevant units from the point of view of Information Retrieval. We present here the main principles of our semantic modeling approach to temporal adverbial units. It comprises two steps: functional modeling (using a small number of basic operators) and referential modeling (using calendar intervals). In order to establish relationships between calendar zones, our approach takes into account not only the calendar values involved in adverbial units but also the semantics of prepositional phrases involved in these units. Through a first experiment, we show how Information Retrieval systems could benefit from indexing calendar expressions in texts, defining relevance scores that combine keywords and temporal ranking models.

Polychrome tree grammars (PTGs): a formal presentation

Publisher Summary This chapter provides an overview of polychrome tree grammars (PTGs). The motivation of PTGs is twofold: (1) to give an autonomous representation of the syntactic positions underlining NL utterances, and (2) to give a monostratal account of extraclausal constituents (ECs) on the syntactic level. PTGs are conceived as a purely syntactic formalism in an autolexical grammar. The chapter focuses on the syntactic level that is conceived as configurations of unlabelled positions. It gives mathematical definitions for polychrome trees, tree composition, and tree grammars. The chapter presents the way in which context-sensitivity (CS) is obtained without CS-rules or feature structures. The autolexical approach requires that the informational patterns of each dimension of NL utterances be exactly characterized by a generative grammar in the broad sense, that is, a grammar that is explicit and formal, and that makes clear and testable predictions. PTGs appear to be a sound formalism for characterizing the syntactic level.

Information Retrieval: Ranking Results According to Calendar Criteria

Our work deals with calendar information as it is expressed in natural language (NL), that is to say through textual units such as prepositional phrases or noun phrases (e.g. in the 90s, at the beginning of the XVth century). We call these textual units Calendar Expressions (CE). Our work aims at showing how Information Retrieval systems can benefit from dealing with CE. In this paper we describe our overall approach which consists in a formal analysis of CEs that leads to a semantic representation. We then detail an algorithm that uses this representation to filter and rank CEs embedded in texts, according to a query containing a CE. The algorithm is integrated in an experimental search engine (called CaSE). Our representation of calendar information as it is expressed in NL and the function which computes the proximity between the two CEs, one in the text and the other in the query, provides a mean to process a query without any overlapping.