Triple

T9766468
Position Surface form Disambiguated ID Type / Status
Subject Konstanz E237005 entity
Predicate twinnedWith P1072 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: [Konstanz, twinnedWith, Fontainebleau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fontainebleau
Context triple: [Konstanz, twinnedWith, 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. L’Haÿ-les-Roses
    L’Haÿ-les-Roses is a suburban commune in the southern outskirts of Paris, France, known for its historic rose garden and residential 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_69ca84d831b8819090322686b47887ce completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda0a15e408190909745cb1c30937d completed April 1, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1bcf965e88190b505ce160f77e9b7 completed April 5, 2026, 1:38 a.m.
Created at: March 30, 2026, 8:25 p.m.