Triple

T5025092
Position Surface form Disambiguated ID Type / Status
Subject Esplanade de La Défense E112954 entity
Predicate near P350 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: [Esplanade de La Défense, near, Nanterre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nanterre
Context triple: [Esplanade de La Défense, near, 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. Trappes
    Trappes is a suburban commune in north-central France, located in the Yvelines department within the Île-de-France region near Paris.
  • 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_69bd4435c2f48190be593158cbfcf8a3 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd736a0f8c819091d06275954329e9 completed March 20, 2026, 4:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8de86454081909232f45fa7d48976 completed March 29, 2026, 8:10 a.m.
Created at: March 20, 2026, 1:36 p.m.