Triple

T7213203
Position Surface form Disambiguated ID Type / Status
Subject Fontainebleau–Avon station E149460 entity
Predicate connectsTo P845 FINISHED
Object Montereau E343349 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: Montereau | Statement: [Fontainebleau–Avon station, connectsTo, Montereau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Montereau
Context triple: [Fontainebleau–Avon station, connectsTo, Montereau]
  • A. Montereau-Fault-Yonne chosen
    Montereau-Fault-Yonne is a commune in north-central France where the Yonne River meets the Seine, historically noted as a strategic river junction and site of significant battles.
  • B. Montriond
    Montriond is a small Alpine village and ski resort area in the Haute-Savoie department of southeastern France, known for its proximity to Morzine and the Portes du Soleil ski domain.
  • C. Remigny
    Remigny is a small wine-producing village in the Burgundy region of eastern France, situated near the renowned appellation of Santenay.
  • D. Les Mureaux
    Les Mureaux is a suburban commune in north-central France known for its aerospace industry and location along the Seine, west of Paris.
  • E. Hurepoix
    Hurepoix is a historic region of northern France, southwest of Paris, known for its rural landscapes and small towns such as Dourdan.
  • 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_69c687eca814819095abb52316b1af80 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6e98b61448190add3624a818fdc7b completed March 27, 2026, 8:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c83c4097d88190b00a8c64ce6871e5 completed March 28, 2026, 8:38 p.m.
Created at: March 27, 2026, 2:53 p.m.