Temporal Expression Identification Based on Semantic Roles

Llorens, Hector; Saquete, Estela; Navarro, Borja

doi:10.1007/978-3-642-12550-8_19

Cited by 11 publications

(22 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The rule-based strategy can be applied to timex recognition owing to the relationship that timexes have with temporal semantic classes and semantic roles (Llorens, Navarro, & Saquete, 2009a;Llorens, Saquete, & Navarro, 2009b). However, the relatedness of semantics with events is more complex, particularly with regard to semantic roles.…”

Section: Our Proposal: Tipsemmentioning

confidence: 98%

Applying semantic knowledge to the automatic processing of temporal expressions and events in natural language

Llorens

Saquete

Navarro-Colorado

2013

Information Processing & Management

Self Cite

View full text Add to dashboard Cite

Section: Our Proposal: Tipsemmentioning

confidence: 98%

Applying semantic knowledge to the automatic processing of temporal expressions and events in natural language

Llorens

Saquete

Navarro-Colorado

2013

Information Processing & Management

Self Cite

View full text Add to dashboard Cite

“…Stanford SUTime [11] is a tested technology and available to be used as a programming library. An alternative is TIPSem [12] which has been tested and available as API.…”

Section: Time Expression Recognition: Time Expression Recognition Tasmentioning

confidence: 99%

A Document Profile for Improving Information Retrieval Systems

Guillén¹,

Gutiérrez²,

Muñoz³

2017

RCS

View full text Add to dashboard Cite

In recent year the great popularity that enjoys mobile technologies has led most users to become consumers and producers of information on the network. Many studies speak about this phenomenon as an activity that is capable of doubling or tripling existing content on an annual basis. The huge amount of information makes the current user oriented systems, like retrieval systems, recommender systems and others, become less ecient, especially when users require specic information and answers according to their needs and preferences. These facts make necessary to equip these systems with proper Natural Language technologies able to provide the information that users demand adapted to each context and content type. In this article, it is presented a study of some Natural Language Processing technologies that can be useful to facilitate the proper identication of documents according to the user needs. For this purpose, it is designed a document prole that will be able to represent semantic meta-data extracted from documents. The research is basically focused on the study of dierent language technologies in order to support the creation this novel document prole proposal from semantic perspectives.

show abstract

“…Only one out of seven participants in the event extraction and classification subtask uses a rule-based approach (Zavarella and Tanev 2013). The best performing systems rely on a supervised approach both for event extraction and event type classification: TIPSem (Llorens, Saquete and Navarro 2010), ATT1 (Jung and Stent 2013) and KUL (Kolomiyets and Moens 2013) are based on Conditional Random Fields, MaxEnt classification and Logistic Regression, respectively. They all take advantage of morphosyntactic information (e.g., POS) and semantic features at both the lexical and the sentence level, e.g., WordNet synsets (Fellbaum 1998) and semantic roles.…”

Section: The Ie Perspective On Eventsmentioning

confidence: 99%

“…The evaluation on Spanish data, instead, is remarkably different. We evaluated the TIPSem system (Llorens et al 2010) on the Modes TimeBank, and we compared it with the TempEval 2013 results of the same system (UzZaman et al 2013). In this case, the performance in the two domains is very different: On news data, the system achieves F1 0.89 (P 0.92, R 0.86), whilst its performance drops to F1 0.39 (P 0.27, R 0.72) on the ModeS TimeBank, since the corpus shows many diachronical language variations affecting precision.…”

Section: The Ie Perspective On Eventsmentioning

confidence: 99%

One, no one and one hundred thousand events: Defining and processing events in an inter-disciplinary perspective

Sprugnoli¹,

Tonelli²

2016

Nat. Lang. Eng.

View full text Add to dashboard Cite

We present an overview of event definition and processing spanning 25 years of research in NLP. We first provide linguistic background to the notion of event, and then present past attempts to formalize this concept in annotation standards to foster the development of benchmarks for event extraction systems. This ranges from MUC-3 in 1991 to the Time and Space Track challenge at SemEval 2015. Besides, we shed light on other disciplines in which the notion of event plays a crucial role, with a focus on the historical domain. Our goal is to provide a comprehensive study on event definitions and investigate which potential past efforts in the NLP community may have in a different research domain. We present the results of a questionnaire, where the notion of event for historians is put in relation to the NLP perspective.

show abstract

Temporal Expression Identification Based on Semantic Roles

Cited by 11 publications

References 16 publications

Applying semantic knowledge to the automatic processing of temporal expressions and events in natural language

Applying semantic knowledge to the automatic processing of temporal expressions and events in natural language

A Document Profile for Improving Information Retrieval Systems

One, no one and one hundred thousand events: Defining and processing events in an inter-disciplinary perspective

Contact Info

Product

Resources

About