Triple

T2160015
Position Surface form Disambiguated ID Type / Status
Subject Metro Line 3 E47977 entity
Predicate hasRollingStockType P1305 FINISHED
Object NM-83B
NM-83B is a type of electric multiple unit rolling stock used to operate trains on Mexico City Metro Line 3.
 E240237 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: NM-83B | Statement: [Metro Line 3, hasRollingStockType, NM-83B]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: NM-83B
Context triple: [Metro Line 3, hasRollingStockType, NM-83B]
  • A. N84
    N84 is a regional road that serves as a key junction route connecting to the town of Bastogne in Belgium.
  • B. NM 4
    NM 4 is a state highway in New Mexico that runs through the Jemez Mountains, providing access to scenic landscapes, small communities, and nearby national monuments.
  • C. B82
    B82 is a New York City bus route that runs through Brooklyn, connecting neighborhoods such as Canarsie with other parts of the borough.
  • D. NMB
    NMB is a German vehicle registration code assigned to the Burgenlandkreis district in the state of Saxony-Anhalt.
  • E. NMTI
    NMTI is a prestigious United States presidential award that honors individuals, teams, and companies for outstanding contributions to technological innovation and advancement.
  • 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: NM-83B
Triple: [Metro Line 3, hasRollingStockType, NM-83B]
Generated description
NM-83B is a type of electric multiple unit rolling stock used to operate trains on Mexico City Metro Line 3.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: NM-83B
Target entity description: NM-83B is a type of electric multiple unit rolling stock used to operate trains on Mexico City Metro Line 3.
  • A. N84
    N84 is a regional road that serves as a key junction route connecting to the town of Bastogne in Belgium.
  • B. NM 4
    NM 4 is a state highway in New Mexico that runs through the Jemez Mountains, providing access to scenic landscapes, small communities, and nearby national monuments.
  • C. B82
    B82 is a New York City bus route that runs through Brooklyn, connecting neighborhoods such as Canarsie with other parts of the borough.
  • D. NMB
    NMB is a German vehicle registration code assigned to the Burgenlandkreis district in the state of Saxony-Anhalt.
  • E. NMTI
    NMTI is a prestigious United States presidential award that honors individuals, teams, and companies for outstanding contributions to technological innovation and advancement.
  • 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_69a88a1d1fd8819088b34990d69a712f completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abbe8894d481908eda9363fd36fea6 completed March 7, 2026, 5:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae58e9ceb08190871ff9c57ece23c0 completed March 9, 2026, 5:21 a.m.
NEDg Description generation batch_69ae5a3db428819083d73b4295c4e829 completed March 9, 2026, 5:27 a.m.
NED2 Entity disambiguation (via description) batch_69ae5a9b72188190bceb31975461206f completed March 9, 2026, 5:28 a.m.
Created at: March 4, 2026, 7:45 p.m.