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
Competition
Language
Spanish
English
NLP topic
Abstract task
Dataset
Year
2021
Publication link
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 |

