Entity recognition

The goal of this task is to identify all the entities in a document and their types. These entities are all the relevant terms (single word or multiple words) that represent semantically important elements in a sentence. Entities always consist of one or more complete words (i.e., not a prefix or a suffix of a word), and never include any surrounding punctuation symbols, parenthesis, etc.

Four types of entities are considered:

  • Concept: identifies a relevant term, concept, idea, in the knowledge domain of the sentence.
  • Action: identifies a process or modification of other entities. It can be indicated by a verb or verbal construction, and also by nouns.
  • Predicate: identifies a function or filter of another set of elements, which has a semantic label in the text, and is applied to an entity with some additional arguments.
  • Reference: identifies a textual element that refers to an entity of the same sentence or of different one.
Publication
Alejandro Piad-Morfis, Suilan Estevez-Velarde, Yoan Gutierrez, Yudivian Almeida-Cruz, Andrés Montoyo, Rafael Muñoz (2021) Overview of the eHealth Knowledge Discovery Challenge at IberLEF 2021. Procesamiento del Lenguaje Natural, Revista nº 67, septiembre de 2021, pp. 233-242
Language
Spanish
English
Abstract task
Dataset
Year
2021
Ranking metric
F1

Task results

System Precision Recall F1 Sort ascending
PUCRJ-PUCPR-UFMG 0.7140 0.6970 0.7060
Vicomtech 0.6990 0.7470 0.6840
IXA 0.6130 0.6980 0.6530
UH-MMM 0.5460 0.6850 0.6070
uhKD4 0.5170 0.5370 0.5270

If you have published a result better than those on the list, send a message to odesia-comunicacion@lsi.uned.es indicating the result and the DOI of the article, along with a copy of it if it is not published openly.