Triple

T12575831
Position Surface form Disambiguated ID Type / Status
Subject Metropolitan Rapid Transit E300202 entity
Predicate abbreviation P43 FINISHED
Object MRT
MRT is a common abbreviation for urban metro or subway systems providing high-capacity public transportation in major cities.
 E990550 NE FINISHED

How this triple was built (4 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: [Metropolitan Rapid Transit, abbreviation, MRT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MRT
Context triple: [Metropolitan Rapid Transit, abbreviation, 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 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.
  • D. MRT2
    MRT2 is the common name for the MRT Putrajaya Line, a major mass rapid transit line serving the Klang Valley region in Malaysia.
  • E. MRT Dark Red Line
    MRT Dark Red Line is a mass rapid transit route on the MRT subway system, serving as one of its primary urban rail lines.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: MRT
Triple: [Metropolitan Rapid Transit, abbreviation, MRT]
Generated description
MRT is a common abbreviation for urban metro or subway systems providing high-capacity public transportation in major cities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MRT
Target entity description: MRT is a common abbreviation for urban metro or subway systems providing high-capacity public transportation in major cities.
  • 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 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.
  • D. MRT2
    MRT2 is the common name for the MRT Putrajaya Line, a major mass rapid transit line serving the Klang Valley region in Malaysia.
  • E. MRT Dark Red Line
    MRT Dark Red Line is a mass rapid transit route on the MRT subway system, serving as one of its primary urban rail lines.
  • F. None of above. chosen

Provenance (5 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_69f65597dc70819089ddc1794e9bd1b7 completed May 2, 2026, 7:50 p.m.
NEDg Description generation batch_69f656f812bc8190a2a691285fc30e03 completed May 2, 2026, 7:56 p.m.
NED2 Entity disambiguation (via description) batch_69f657ea0c6c8190992a0101904e92f2 completed May 2, 2026, 8 p.m.
Created at: April 9, 2026, 4:47 p.m.