Triple

T27797526
Position Surface form Disambiguated ID Type / Status
Subject Anglo-Italian Cup E702154 entity
Predicate founder P104 FINISHED
Object Gigi Peronace
Gigi Peronace was an influential Italian football agent and administrator known for pioneering high-profile international transfers and helping to popularize European club competitions.
E1803410 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: Gigi Peronace | Statement: [Anglo-Italian Cup, founder, Gigi Peronace]
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: Gigi Peronace
Triple: [Anglo-Italian Cup, founder, Gigi Peronace]
Generated description
Gigi Peronace was an influential Italian football agent and administrator known for pioneering high-profile international transfers and helping to popularize European club competitions.

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_69ef8408e0588190977cffa32dc33a29 completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f6380c776c8190afe636c9e65301a0 completed May 2, 2026, 5:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15c8e43c488190afe8e6491587e96c completed May 26, 2026, 4:23 p.m.
NEDg Description generation batch_6a15cb20629c81908e81ef6da4f676b1 completed May 26, 2026, 4:32 p.m.
NED2 Entity disambiguation (via description) batch_6a15cbc2fa6c8190a3d8a4b60ab6104c completed May 26, 2026, 4:35 p.m.
Created at: April 27, 2026, 5:32 p.m.