Triple

T12575898
Position Surface form Disambiguated ID Type / Status
Subject BEM E300204 entity
Predicate partOf P40 FINISHED
Object MRT unclear NED1 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: MRT | Statement: [BEM, partOf, MRT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MRT
Context triple: [BEM, partOf, MRT]
  • A. MRT
    MRT is the three-letter ISO 3166-1 alpha-3 country code assigned to Mauritania.
  • B. MRT
    MRT is the commonly used abbreviation for the Taipei Metro, the rapid transit system serving Taipei and its surrounding areas.
  • C. MRT
    MRT is a common abbreviation for urban metro or subway systems providing high-capacity public transportation in major cities.
  • D. MRT subway
    The MRT subway in Bangkok is a major rapid transit system that provides fast, air-conditioned underground and elevated rail services across key areas of the city.
  • E. MRT2
    MRT2 is the common name for the MRT Putrajaya Line, a major mass rapid transit line serving the Klang Valley region in Malaysia.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69d7bde87b648190bcd0266e9efde098 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954a629fc8190a1c3b6777aad4527 completed April 10, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65eb8ec888190b46a0b48840efd20 completed May 2, 2026, 8:29 p.m.
Created at: April 9, 2026, 4:47 p.m.