Triple

T7784817
Position Surface form Disambiguated ID Type / Status
Subject Philip VI of France E187214 entity
Predicate birthPlace P1 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: [Philip VI of France, birthPlace, Fontainebleau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fontainebleau
Context triple: [Philip VI of France, birthPlace, 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_69ca82af2d2c8190963861f5e0b8bf21 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cadf210f508190b215a0ab95192689 completed March 30, 2026, 8:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69caf5f4fa6c8190a85ba9019c0e5345 completed March 30, 2026, 10:15 p.m.
Created at: March 30, 2026, 4:23 p.m.