Triple

T27886869
Position Surface form Disambiguated ID Type / Status
Subject FC Barcelona futsal team E705254 entity
Predicate competition P563 FINISHED
Object Copa de España de Futsal
The Copa de España de Futsal is one of Spain’s premier national futsal cup tournaments, featuring the country’s top professional clubs in a knockout format.
E1793797 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Copa de España de Futsal | Statement: [FC Barcelona futsal team, competition, Copa de España de Futsal]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Copa de España de Futsal
Triple: [FC Barcelona futsal team, competition, Copa de España de Futsal]
Generated description
The Copa de España de Futsal is one of Spain’s premier national futsal cup tournaments, featuring the country’s top professional clubs in a knockout format.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ef96b39c448190a9b3aa6672a5168f completed April 27, 2026, 5:02 p.m.
NER Named-entity recognition batch_69f639b198bc8190ac1e931d757b015e completed May 2, 2026, 5:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a13035bed2c8190a0b72658cbf54689 completed May 24, 2026, 1:55 p.m.
NEDg Description generation batch_6a1304e90e708190b66c35687b00ae91 completed May 24, 2026, 2:02 p.m.
NED2 Entity disambiguation (via description) batch_6a13057d68408190bb5e5855121f5195 completed May 24, 2026, 2:04 p.m.
Created at: April 27, 2026, 6:33 p.m.