Triple

T38655828
Position Surface form Disambiguated ID Type / Status
Subject 1974 World Football League season E939887 entity
Predicate commissioner P3178 FINISHED
Object Gary L. Davidson
Gary L. Davidson is an American sports entrepreneur best known for co-founding and leading upstart professional leagues such as the World Football League, World Hockey Association, and American Basketball Association.
E2297314 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: Gary L. Davidson | Statement: [1974 World Football League season, commissioner, Gary L. Davidson]
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: Gary L. Davidson
Triple: [1974 World Football League season, commissioner, Gary L. Davidson]
Generated description
Gary L. Davidson is an American sports entrepreneur best known for co-founding and leading upstart professional leagues such as the World Football League, World Hockey Association, and American Basketball Association.

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_69f76ede49648190a48bfe47032a05a3 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fcdbe8c56c8190ab80c9847566fa83 completed May 7, 2026, 6:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a835bbd6ad88190b4a3e4fe6e880f0b completed Aug. 17, 2026, 7:06 p.m.
NEDg Description generation batch_6a835cd53e74819087a2c529afe10e47 completed Aug. 17, 2026, 7:11 p.m.
NED2 Entity disambiguation (via description) batch_6a835d261e188190965bb32d13e8a7ff completed Aug. 17, 2026, 7:12 p.m.
Created at: May 3, 2026, 4:33 p.m.