Triple

T10847397
Position Surface form Disambiguated ID Type / Status
Subject Paris–Rennes railway E256048 entity
Predicate servesCity P82 FINISHED
Object Laval E362220 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: [Paris–Rennes railway, servesCity, Laval]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laval
Context triple: [Paris–Rennes railway, servesCity, Laval]
  • A. Laval chosen
    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.
  • B. Laval
    Laval is a large suburban city and island located just north of Montreal in southwestern Quebec, Canada.
  • C. Laval
    Laval is a French surname most notably associated with Pierre Laval, a prominent and controversial political figure during the Vichy regime in World War II.
  • D. Sherbrooke
    Sherbrooke is a major city in southern Quebec, Canada, known as an important economic, cultural, and educational center in the Eastern Townships region.
  • E. 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.
  • 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_69d6aa81a5d08190aa86689061d1ddd2 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d75113bc188190ac78df0c51d95de6 completed April 9, 2026, 7:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69deb170e714819097babb2b850342d2 completed April 14, 2026, 9:28 p.m.
Created at: April 8, 2026, 9:20 p.m.