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Impact on the Sustainable Development Goals (SDGs)

Analysis of institutional authors

Navas-Loro, MariaCorresponding AuthorRodriguez-Doncel, VictorAuthor

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October 4, 2020
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Annotador: a temporal tagger for Spanish

Publicated to: JOURNAL OF INTELLIGENT & FUZZY SYSTEMS. 39 (2): 1979-1991 - 2020-01-01 39(2), DOI: 10.3233/JIFS-179865

Authors:

Navas-Loro, M; Rodríguez-Doncel, V
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Affiliations

Univ Politecn Madrid, Ontol Engn Grp, Campus Montegancedo S-N, Madrid 28660, Spain - Author

Abstract

Temporal information is crucial in knowledge extraction. Being able to locate events in a timeline is necessary to understand the narrative behind every text. To this aim, several temporal taggers have been proposed in literature -nevertheless, not all languages received the same attention. Most taggers work only for English texts, and not many have been developed for other languages. Also the scarcity of annotated corpora in other languages notably hinders the task. In this paper we present a new rule-based tagger called Annotador (Anotador in Spanish) able to process texts both in Spanish and English. Furthermore, a new corpus with more than 300 short texts containing common temporal expressions, called the HourGlass corpus, has been built in order to test it and to facilitate the development of new resources and tools. Professionals from different domains intervened in the gathering of the text, making it heterogeneous and easy to use thanks to the tags added to each entry. Finally, we analyzed main challenges in the time expression extraction task.
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Keywords

NlpQuality educationSpanish languageTemporal taggerTime expression

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal JOURNAL OF INTELLIGENT & FUZZY SYSTEMS due to its progression and the good impact it has achieved in recent years, according to the agency Scopus (SJR), it has become a reference in its field. In the year of publication of the work, 2020, it was in position , thus managing to position itself as a Q2 (Segundo Cuartil), in the category Artificial Intelligence.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-25:

  • Google Scholar: 19
  • WoS: 10
  • Scopus: 12
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-25:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 6 (PlumX).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/93339/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 25
  • Downloads: 10
Continuing with the social impact of the work, it is important to emphasize that, due to its content, it can be assigned to the area of interest of ODS 4 - Quality Education, with a probability of 76% according to the mBERT algorithm developed by Aurora University.
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Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (NAVAS LORO, MARIA) and Last Author (RODRIGUEZ DONCEL, VICTOR).

the author responsible for correspondence tasks has been NAVAS LORO, MARIA.

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Project objectives

La aportación persigue los siguientes objetivos: desarrollar un etiquetador temporal basado en reglas capaz de procesar textos en español e inglés; construir un nuevo corpus denominado HourGlass con más de 300 textos cortos que contienen expresiones temporales comunes; facilitar el desarrollo de recursos y herramientas mediante la creación de un corpus heterogéneo y anotado por profesionales de distintos ámbitos; analizar los principales desafíos en la tarea de extracción de expresiones temporales; y contribuir a superar la escasez de corpus anotados en idiomas distintos al inglés.
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Most relevant results

Los resultados más relevantes de esta aportación se centran en el desarrollo y evaluación de una herramienta para el etiquetado temporal en textos en español e inglés. En primer lugar, se presenta Annotador, un etiquetador basado en reglas capaz de procesar ambos idiomas. En segundo lugar, se ha construido el corpus HourGlass, compuesto por más de 300 textos breves con expresiones temporales comunes, diseñado para evaluar el etiquetador y fomentar la creación de recursos similares. En tercer lugar, la heterogeneidad del corpus se asegura mediante la participación de profesionales de diversos ámbitos y la inclusión de etiquetas detalladas en cada texto. Finalmente, se identifican y analizan los principales desafíos en la extracción de expresiones temporales.
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Awards linked to the item

This paper has been supported by the Lynx H2020 project (grant agreement No. 780602), and is part of a PhD thesis funded by a Predoctoral grant of the Universidad Politecnica de Madrid. We would also want to thank all the contributors to our corpus.
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