Triple

T37011675
Position Surface form Disambiguated ID Type / Status
Subject Vancouver Blazers E915965 entity
Predicate notablePlayer P304 FINISHED
Object Bryan Campbell
Bryan Campbell is a former professional ice hockey player best known for his time in the World Hockey Association, including a notable stint with the Vancouver Blazers.
E2223754 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: Bryan Campbell | Statement: [Vancouver Blazers, notablePlayer, Bryan Campbell]
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: Bryan Campbell
Triple: [Vancouver Blazers, notablePlayer, Bryan Campbell]
Generated description
Bryan Campbell is a former professional ice hockey player best known for his time in the World Hockey Association, including a notable stint with 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_69fa004559408190b703411eae0b75cb completed May 5, 2026, 2:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a406cbe64248190b04419fe2109596a completed June 28, 2026, 12:37 a.m.
NEDg Description generation batch_6a406defac38819086c2585b63b93dde completed June 28, 2026, 12:42 a.m.
NED2 Entity disambiguation (via description) batch_6a406e7763b081908b37db6d670f2084 completed June 28, 2026, 12:44 a.m.
Created at: May 3, 2026, 4:14 p.m.