Triple

T8883735
Position Surface form Disambiguated ID Type / Status
Subject Line 4 (Paris Métro) E211472 entity
Predicate rollingStock P1305 FINISHED
Object MP 05 trains E199956 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: MP 05 trains | Statement: [Line 4 (Paris Métro), rollingStock, MP 05 trains]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MP 05 trains
Context triple: [Line 4 (Paris Métro), rollingStock, MP 05 trains]
  • A. MP 05 trains chosen
    MP 05 trains are modern, rubber-tyred, automated metro trainsets used on several lines of the Paris Métro.
  • B. MP-68 trains
    MP-68 trains are a class of rubber-tyred metro rolling stock that have operated on Mexico City’s Metro system since the late 1960s.
  • C. MP 89 trains
    MP 89 trains are a class of rubber-tyred, automated-capable Paris Métro rolling stock known for their modern design and use on several key lines of the network.
  • D. MP 14 trains
    MP 14 trains are a modern generation of rubber-tyred Paris Métro trains designed for automated operation, improved energy efficiency, and enhanced passenger comfort.
  • E. M100 series trains
    The M100 series trains are the original electric multiple units that have operated on the Helsinki Metro since its opening, known for their robust design and long service life.
  • 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_69ca838f9e20819096ab1f236a70381a completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc616b2d988190b923ef1e33aab787 completed April 1, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfabd254148190b5ea3d308fe96851 completed April 3, 2026, noon
Created at: March 30, 2026, 6:53 p.m.