Triple

T9875889
Position Surface form Disambiguated ID Type / Status
Subject Quartier de Picpus E240070 entity
Predicate administrativeDivisionNumberInParis P26130 FINISHED
Object 49 LITERAL 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: 49 | Statement: [Quartier de Picpus, administrativeDivisionNumberInParis, 49]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: administrativeDivisionNumberInParis
Context triple: [Quartier de Picpus, administrativeDivisionNumberInParis, 49]
  • A. officeStartTime (Mayor of 7th arrondissement)
    Indicates the time at which the Mayor of the 7th arrondissement officially begins their term in office.
  • B. hasArrondissement chosen
    Indicates a relationship where an administrative unit or locality is associated with, or belongs to, a specific arrondissement.
  • C. inseeCode
    Indicates the official INSEE (French national statistics institute) code assigned to an entity, typically identifying a specific geographic or administrative unit.
  • D. capitalOfCommune
    Indicates that one place serves as the administrative capital or chief town of a given commune.
  • E. formerINSEECode
    Indicates that an entity was previously identified by a different INSEE code before being assigned its current one.
  • F. None of above.

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_69ca84e8a0788190b9061811d50fd554 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3f9d82c81908afb4977ce4e3e4a completed April 2, 2026, 12:10 a.m.
PD Predicate disambiguation batch_69cd1d810ed48190a252b70e9390c8f3 completed April 1, 2026, 1:28 p.m.
Created at: March 30, 2026, 8:37 p.m.