Triple

T29357361
Position Surface form Disambiguated ID Type / Status
Subject Miguel Pérez Cuesta E744481 entity
Predicate memberOfSportsTeam P330 FINISHED
Object Real Oviedo Vetusta
Real Oviedo Vetusta is the reserve team of Spanish football club Real Oviedo, competing in the lower tiers of the Spanish league system and serving as a development side for younger players.
E1866289 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: Real Oviedo Vetusta | Statement: [Miguel Pérez Cuesta, memberOfSportsTeam, Real Oviedo Vetusta]
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: Real Oviedo Vetusta
Triple: [Miguel Pérez Cuesta, memberOfSportsTeam, Real Oviedo Vetusta]
Generated description
Real Oviedo Vetusta is the reserve team of Spanish football club Real Oviedo, competing in the lower tiers of the Spanish league system and serving as a development side for younger players.

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_69f0a79aee588190b490f19d93c6e52d completed April 28, 2026, 12:27 p.m.
NER Named-entity recognition batch_69f66985cdf881909808aaca2394310d completed May 2, 2026, 9:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25d90d8af88190a141b061c6d835f9 completed June 7, 2026, 8:48 p.m.
NEDg Description generation batch_6a25dd222bd08190a914da64e42bc349 completed June 7, 2026, 9:05 p.m.
NED2 Entity disambiguation (via description) batch_6a25e1389e288190a3dda8cf6942d448 completed June 7, 2026, 9:23 p.m.
Created at: April 28, 2026, 2:13 p.m.