Triple

T7213191
Position Surface form Disambiguated ID Type / Status
Subject Fontainebleau–Avon station E149460 entity
Predicate serves P98 FINISHED
Object Fontainebleau E25615 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: Fontainebleau | Statement: [Fontainebleau–Avon station, serves, Fontainebleau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fontainebleau
Context triple: [Fontainebleau–Avon station, serves, Fontainebleau]
  • A. Fontainebleau, France chosen
    Fontainebleau, France is a historic town southeast of Paris best known for its vast forest and royal château, long associated with French monarchs and outdoor recreation.
  • B. Palaiseau
    Palaiseau is a suburban commune in the southern outskirts of Paris, France, known for hosting major scientific and engineering institutions.
  • C. Trappes
    Trappes is a suburban commune in north-central France, located in the Yvelines department within the Île-de-France region near Paris.
  • D. Saint-Germain-en-Laye
    Saint-Germain-en-Laye is a historic town in the western suburbs of Paris, France, known for its royal château and long association with the French monarchy.
  • E. Neuilly-sur-Seine
    Neuilly-sur-Seine is an affluent suburban commune just west of central Paris, known for its upscale residential neighborhoods and proximity to major business districts like La Défense.
  • 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_69c7bfcec3448190ab29c3742aa167ae completed March 28, 2026, 11:47 a.m.
Created at: March 27, 2026, 2:53 p.m.