Triple

T3897692
Position Surface form Disambiguated ID Type / Status
Subject CYMX E90408 entity
Predicate servesCity P82 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: [CYMX, servesCity, Montreal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Montreal
Context triple: [CYMX, servesCity, 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. Lévis
    Lévis is a city located on the south shore of the St. Lawrence River in Quebec, Canada, directly across from Quebec City.
  • 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_69aed95d315881908cbf1bf4a7215fbf completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeecd48b208190afaa62975805d087 completed March 9, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b54c2971788190b8f48da3883d2ba2 completed March 14, 2026, 11:53 a.m.
Created at: March 9, 2026, 3:21 p.m.