Triple

T26366179
Position Surface form Disambiguated ID Type / Status
Subject Brampton Battalion E660339 entity
Predicate notableAlumni P51 FINISHED
Object Wojtek Wolski
Wojtek Wolski is a Polish-Canadian former professional ice hockey forward who played in the NHL for several teams, including the Colorado Avalanche, Phoenix Coyotes, and New York Rangers.
E1813641 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: Wojtek Wolski | Statement: [Brampton Battalion, notableAlumni, Wojtek Wolski]
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: Wojtek Wolski
Triple: [Brampton Battalion, notableAlumni, Wojtek Wolski]
Generated description
Wojtek Wolski is a Polish-Canadian former professional ice hockey forward who played in the NHL for several teams, including the Colorado Avalanche, Phoenix Coyotes, and New York Rangers.

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_69ee8126d52c8190bc0b34337c2c9aa8 completed April 26, 2026, 9:18 p.m.
NER Named-entity recognition batch_69f6102c248c8190886da68d61d006dc completed May 2, 2026, 2:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a162780dc0c81908e1b9b7f0dfb8e8c completed May 26, 2026, 11:06 p.m.
NEDg Description generation batch_6a1628f366d88190b10dda8b0ab63762 completed May 26, 2026, 11:12 p.m.
NED2 Entity disambiguation (via description) batch_6a16297370d08190a0088aa14476bb1f completed May 26, 2026, 11:14 p.m.
Created at: April 26, 2026, 10:55 p.m.