Triple

T32561937
Position Surface form Disambiguated ID Type / Status
Subject European Tour Order of Merit E832249 entity
Predicate category P87 FINISHED
Object European Tour awards
European Tour awards are honors presented annually to recognize outstanding performances and achievements by professional golfers on the European Tour.
E1562233 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: European Tour awards | Statement: [European Tour Order of Merit, category, European Tour awards]
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: European Tour awards
Triple: [European Tour Order of Merit, category, European Tour awards]
Generated description
European Tour awards are honors presented annually to recognize outstanding performances and achievements by professional golfers on the European Tour.

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_69f34926b9848190ace47d2dd0a0de7c completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c6084a348190a1b644c398d91589 completed May 3, 2026, 3:50 a.m.
NED1 Entity disambiguation (via context triple) batch_6a347b95a034819081d54e4669b5cb8f completed June 18, 2026, 11:13 p.m.
NEDg Description generation batch_6a347c29d29c819085157ac0ed98a2f0 completed June 18, 2026, 11:15 p.m.
NED2 Entity disambiguation (via description) batch_6a347d818bf08190b03290203b8ad992 completed June 18, 2026, 11:21 p.m.
Created at: May 1, 2026, 1:03 a.m.