Triple

T26038545
Position Surface form Disambiguated ID Type / Status
Subject Premier League 1998–99 E647619 entity
Predicate PFAPlayersPlayerOfTheYear P16058 FINISHED
Object David Ginola
David Ginola is a retired French winger renowned for his flair and creativity, who starred in English football during the 1990s for clubs such as Newcastle United and Tottenham Hotspur.
E1709022 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: David Ginola | Statement: [Premier League 1998–99, PFAPlayersPlayerOfTheYear, David Ginola]
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: David Ginola
Triple: [Premier League 1998–99, PFAPlayersPlayerOfTheYear, David Ginola]
Generated description
David Ginola is a retired French winger renowned for his flair and creativity, who starred in English football during the 1990s for clubs such as Newcastle United and Tottenham Hotspur.

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_69e77e8c88f08190858c4c81bd2e1b9a completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f60620fb648190826cfb2fdefe4858 completed May 2, 2026, 2:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a111b17b6e4819091e02d58baa659d0 completed May 23, 2026, 3:12 a.m.
NEDg Description generation batch_6a111c26bd588190bcb5b6acd9978f06 completed May 23, 2026, 3:16 a.m.
NED2 Entity disambiguation (via description) batch_6a111cfb960c8190ab95d50846acfb91 completed May 23, 2026, 3:20 a.m.
Created at: April 22, 2026, 9:08 a.m.