Triple

T4313402
Position Surface form Disambiguated ID Type / Status
Subject Cinema Under the Stars E94127 entity
Predicate associatedWithCity P1481 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: [Cinema Under the Stars, associatedWithCity, Montreal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Montreal
Context triple: [Cinema Under the Stars, associatedWithCity, 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_69b3451886588190a3dd1305ea7c58dc completed March 12, 2026, 10:58 p.m.
NER Named-entity recognition batch_69b350f319c08190bb40a9fc5933728d completed March 12, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b67ba3fef08190a0f92460703b0a98 completed March 15, 2026, 9:28 a.m.
Created at: March 12, 2026, 11:12 p.m.