Triple

T611668
Position Surface form Disambiguated ID Type / Status
Subject Bir-Hakeim E12112 entity
Predicate operator P179 FINISHED
Object RATP E27062 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: RATP | Statement: [Bir-Hakeim, operator, RATP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RATP
Context triple: [Bir-Hakeim, operator, RATP]
  • A. RATP group chosen
    RATP Group is a major French public transport operator that manages much of the Paris metro, tram, and bus networks and provides transit services internationally.
  • B. Île-de-France Mobilités
    Île-de-France Mobilités is the public agency responsible for organizing, coordinating, and funding public transportation services across the Paris metropolitan region.
  • C. Transilien
    Transilien is the suburban and regional rail network operated by SNCF that serves the Île-de-France (Greater Paris) area.
  • D. SNCF
    SNCF is France’s national state-owned railway company, responsible for operating the country’s passenger and freight rail services and much of its rail infrastructure.
  • E. RER network
    The RER network is a rapid transit system of express suburban trains serving Paris and its surrounding metropolitan area, integrating both urban and regional rail services.
  • 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_69a493309df48190a327f748e88049a6 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49e07739481909930a6577c081b9e completed March 1, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69a55a7561dc81908e2e2516c63c18a7 completed March 2, 2026, 9:37 a.m.
Created at: March 1, 2026, 7:35 p.m.