Triple

T1954709
Position Surface form Disambiguated ID Type / Status
Subject Lachine Hospital E42238 entity
Predicate serves P98 FINISHED
Object Lachine E110597 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: Lachine | Statement: [Lachine Hospital, serves, Lachine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lachine
Context triple: [Lachine Hospital, serves, Lachine]
  • A. Lachine chosen
    Lachine is a borough of Montreal, Quebec, known for its historic canal, waterfront, and role as an early fur trade and industrial hub.
  • B. Dollard-des-Ormeaux
    Dollard-des-Ormeaux is a suburban city in the West Island area of Montreal, Quebec, known primarily as a residential community.
  • C. Rivière des Prairies
    Rivière des Prairies is a channel of the Saint Lawrence River that separates the Island of Montreal from Île Jésus in southwestern Quebec, Canada.
  • D. Argenteuil
    Argenteuil is a suburban commune in the northwestern outskirts of Paris, France, known historically as an industrial center and as a subject of Impressionist painters.
  • E. Mont-Royal
    Mont-Royal is a prominent hill and urban park in Montreal, Quebec, known for its panoramic city views and central role in the city's identity.
  • 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_69a8870eea088190a38781990812a9bc completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb353aa8c81909810347f9981a02f completed March 7, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae031a46d481908a6e0d78bfa9c66f completed March 8, 2026, 11:15 p.m.
Created at: March 4, 2026, 7:36 p.m.