Triple

T27825402
Position Surface form Disambiguated ID Type / Status
Subject Pierre Bostonais E702938 entity
Predicate hasNickname P39 FINISHED
Object Tête Jaune
Tête Jaune was a French-Canadian fur trader and explorer of the early 19th century, remembered for his role in opening travel and trade routes through the Rocky Mountains of western Canada.
E1225878 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: Tête Jaune | Statement: [Pierre Bostonais, hasNickname, Tête Jaune]
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: Tête Jaune
Triple: [Pierre Bostonais, hasNickname, Tête Jaune]
Generated description
Tête Jaune was a French-Canadian fur trader and explorer of the early 19th century, remembered for his role in opening travel and trade routes through the Rocky Mountains of western Canada.

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_69ef840ad1e88190b5bff2d1ddec8700 completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f63895e7b48190857b652d83e0d62a completed May 2, 2026, 5:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12f72a541081908e029ed1fc357b70 completed May 24, 2026, 1:03 p.m.
NEDg Description generation batch_6a12f7ba8f048190ac484434da112aeb completed May 24, 2026, 1:06 p.m.
NED2 Entity disambiguation (via description) batch_6a12fbae881c8190a13234bf6ad26f8f completed May 24, 2026, 1:22 p.m.
Created at: April 27, 2026, 5:51 p.m.