Triple

T2377832
Position Surface form Disambiguated ID Type / Status
Subject Ingram School of Nursing E46239 entity
Predicate city P40 FINISHED
Object Montreal E2604 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: Montreal | Statement: [Ingram School of Nursing, city, Montreal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Montreal
Context triple: [Ingram School of Nursing, city, Montreal]
  • A. Montreal chosen
    Montreal is the largest city in Quebec, Canada, known for its vibrant bilingual culture, historic architecture, and status as a major economic and cultural center.
  • B. Quebec City
    Quebec City is the historic capital of the Canadian province of Quebec, renowned for its well-preserved fortified old town and rich French colonial heritage.
  • C. Gatineau
    Gatineau is a city in western Quebec, Canada, located across the Ottawa River from Ottawa and forming part of the National Capital Region.
  • D. Trois-Rivières
    Trois-Rivières is a historic industrial and cultural city in the Canadian province of Quebec, located roughly midway between Montreal and Quebec City.
  • E. Ottawa
    Ottawa is the capital city of Canada, located in eastern Ontario along the Ottawa River and known for its federal government institutions, cultural landmarks, and bilingual character.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a88a1554a48190a0180682bcf099be completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abc79610e8819084abfbccd1dc67c0 completed March 7, 2026, 6:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69b2031a55148190a1b96af35d109259 completed March 12, 2026, 12:04 a.m.
Created at: March 4, 2026, 7:57 p.m.