Triple

T37011677
Position Surface form Disambiguated ID Type / Status
Subject Vancouver Blazers E915965 entity
Predicate notableCoach P550 FINISHED
Object Jack Gordon
Jack Gordon was a professional ice hockey coach best known for leading teams in the World Hockey Association and National Hockey League, including the Vancouver Blazers.
E2208682 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: Jack Gordon | Statement: [Vancouver Blazers, notableCoach, Jack Gordon]
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: Jack Gordon
Triple: [Vancouver Blazers, notableCoach, Jack Gordon]
Generated description
Jack Gordon was a professional ice hockey coach best known for leading teams in the World Hockey Association and National Hockey League, including the Vancouver Blazers.

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_69f76e90ed548190b187d2475f5c807d completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fa004ad5b881908a494578f7cf1f01 completed May 5, 2026, 2:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e5770b15c81908010fd9b8c1d29e3 completed June 26, 2026, 10:41 a.m.
NEDg Description generation batch_6a3e591d57608190bd82a60c74d1ae1d completed June 26, 2026, 10:49 a.m.
NED2 Entity disambiguation (via description) batch_6a3e5f3d909c8190b6799371d945e534 completed June 26, 2026, 11:15 a.m.
Created at: May 3, 2026, 4:14 p.m.