Triple

T10011484
Position Surface form Disambiguated ID Type / Status
Subject Little Italy, Montreal E199383 entity
Predicate adjacentTo P224 FINISHED
Object Villeray E670016 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: Villeray | Statement: [Little Italy, Montreal, adjacentTo, Villeray]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Villeray
Context triple: [Little Italy, Montreal, adjacentTo, Villeray]
  • A. Villeray chosen
    Villeray is a residential neighborhood in Montreal, Quebec, known for its diverse population, local shops, and proximity to Jarry Park.
  • B. Ville-la-Grand
    Ville-la-Grand is a commune in the Haute-Savoie department of southeastern France, situated near the Swiss border in the urban area of Annemasse.
  • C. Firminy
    Firminy is a commune in central France known for its notable modernist architecture, including works by Le Corbusier such as the Maison de la Culture.
  • D. Loison
    Loison is a small river in northeastern France that serves as a tributary of the Chiers.
  • E. Bourgueil
    Bourgueil is a Loire Valley wine appellation in France renowned for its red wines, particularly those made predominantly from Cabernet Franc.
  • 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_69ca8315a1a08190ab310f25620f362b completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cdcd3b68888190b8a325b52d57c5b8 completed April 2, 2026, 1:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69d28211c2448190897fd4078a266154 completed April 5, 2026, 3:38 p.m.
Created at: March 30, 2026, 8:52 p.m.