Triple

T4074112
Position Surface form Disambiguated ID Type / Status
Subject CMM E86719 entity
Predicate governs P760 FINISHED
Object Laval E138766 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: Laval | Statement: [CMM, governs, Laval]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laval
Context triple: [CMM, governs, Laval]
  • A. Laval chosen
    Laval is a large suburban city and island located just north of Montreal in southwestern Quebec, Canada.
  • B. Laval
    Laval is a major city in western France, located in the Mayenne department, known for its historic architecture and role as an administrative and economic center of the region.
  • C. Sherbrooke
    Sherbrooke is a major city in southern Quebec, Canada, known as an important economic, cultural, and educational center in the Eastern Townships region.
  • D. Limoilou
    Limoilou is a primarily residential neighborhood in Quebec City, Canada, known for its dense urban fabric, vibrant local commerce, and historic working-class character.
  • E. Villeneuve-le-Roi
    Villeneuve-le-Roi is a suburban commune in the southeastern outskirts of Paris, France, situated along the Seine River and closely linked to the nearby Orly Airport.
  • 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_69aed93ebe448190a1f1686e28740ac9 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefc245d888190ae773f9c3077953b completed March 9, 2026, 4:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69b562bc05948190a9ad709768420588 completed March 14, 2026, 1:29 p.m.
Created at: March 9, 2026, 3:39 p.m.