Triple

T10001265
Position Surface form Disambiguated ID Type / Status
Subject Puteaux E197331 entity
Predicate sharesLaDéfenseDistrictWith P91225 FINISHED
Object Nanterre E252395 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: Nanterre | Statement: [Puteaux, sharesLaDéfenseDistrictWith, Nanterre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nanterre
Context triple: [Puteaux, sharesLaDéfenseDistrictWith, Nanterre]
  • A. Nanterre chosen
    Nanterre is a western suburb of Paris in the Hauts-de-Seine department of France, known as an important administrative and educational center.
  • B. Étampes
    Étampes is a historic commune and former royal town in northern France, located in the Essonne department in the Île-de-France region.
  • C. Créteil
    Créteil is a southeastern suburb of Paris and the administrative center of the Val-de-Marne department in northern France.
  • D. Bezons
    Bezons is a suburban commune in the northwestern outskirts of Paris, located in the Val-d'Oise department of the Île-de-France region in northern France.
  • E. Fontenay-en-Parisis
    Fontenay-en-Parisis is a small commune in the Val-d'Oise department in the Île-de-France region of northern France.
  • 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_69ca82f3b61c81908ecc2c1c96dbc2e4 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdcc8f50888190b2f1c5240cb58e4f completed April 2, 2026, 1:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69f60a4d8a3481909c7f8a529d0051c2 completed May 2, 2026, 2:29 p.m.
Created at: March 30, 2026, 8:51 p.m.