Triple

T25290302
Position Surface form Disambiguated ID Type / Status
Subject Platense E634063 entity
Predicate fullName P16 FINISHED
Object Club Atlético Platense
Club Atlético Platense is an Argentine sports club best known for its professional football team, which competes in the country’s top divisions and is traditionally associated with the Vicente López area of Greater Buenos Aires.
E1730429 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: Club Atlético Platense | Statement: [Platense, fullName, Club Atlético Platense]
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: Club Atlético Platense
Triple: [Platense, fullName, Club Atlético Platense]
Generated description
Club Atlético Platense is an Argentine sports club best known for its professional football team, which competes in the country’s top divisions and is traditionally associated with the Vicente López area of Greater Buenos Aires.

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_69e75a9503d48190b80a005c6af0cb50 completed April 21, 2026, 11:08 a.m.
NER Named-entity recognition batch_69f48fcc8fe88190bf330715354553f6 completed May 1, 2026, 11:34 a.m.
NED1 Entity disambiguation (via context triple) batch_6a11c7e002708190a33c46e042f7f5c5 completed May 23, 2026, 3:29 p.m.
NEDg Description generation batch_6a11c8bf3ee08190964adc437235340b completed May 23, 2026, 3:33 p.m.
NED2 Entity disambiguation (via description) batch_6a11c981c70c8190bfe0da42958fa494 completed May 23, 2026, 3:36 p.m.
Created at: April 21, 2026, 1:21 p.m.