Triple

T10668899
Position Surface form Disambiguated ID Type / Status
Subject Balderas E251432 entity
Predicate hasStationCode P1289 FINISHED
Object BA
BA is the station code for Balderas, a metro station in Mexico City’s rapid transit system.
E876738 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: BA | Statement: [Balderas, hasStationCode, BA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BA
Context triple: [Balderas, hasStationCode, BA]
  • A. BA
    BA is the New York Stock Exchange ticker symbol for The Boeing Company, a major American aerospace and defense manufacturer.
  • B. BA
    BA is the vehicle registration code used on license plates for cars registered in Bratislava, the capital city of Slovakia.
  • C. BA
    BA is the two-letter ISO 3166-1 alpha-2 country code assigned to Bosnia and Herzegovina.
  • D. BA
    BA is the commonly used abbreviation for the British Academy, the United Kingdom’s national academy for the humanities and social sciences.
  • E. BA
    BA is a common abbreviation for Broken Arrow, a suburban city in northeastern Oklahoma.
  • 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: BA
Triple: [Balderas, hasStationCode, BA]
Generated description
BA is the station code for Balderas, a metro station in Mexico City’s rapid transit system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: BA
Target entity description: BA is the station code for Balderas, a metro station in Mexico City’s rapid transit system.
  • A. BA
    BA is the station code for Bathurst station on the Toronto Transit Commission subway system.
  • B. BA
    BA is a common abbreviation for Broken Arrow, a suburban city in northeastern Oklahoma.
  • C. BA
    BA is the vehicle registration code used on license plates for cars registered in Bratislava, the capital city of Slovakia.
  • D. BA
    BA is the vehicle registration code used on license plates for the city and district of Bamberg in Upper Franconia, Germany.
  • E. BA
    BA is the former stock ticker symbol for Bell Aliant, a Canadian telecommunications company that provided internet, phone, and TV services primarily in Atlantic Canada before being acquired by Bell Canada.
  • 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_69d6aa5b0d2881909584b20efc5877f0 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6f861513881909b44c711371086b7 completed April 9, 2026, 12:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69d97a9e722c8190a5d9f728282b9a52 completed April 10, 2026, 10:33 p.m.
NEDg Description generation batch_69d97cc2b66c8190909a23927fbe3af5 completed April 10, 2026, 10:42 p.m.
NED2 Entity disambiguation (via description) batch_69d97e189800819087bf6af15b2370a2 completed April 10, 2026, 10:47 p.m.
Created at: April 8, 2026, 9:09 p.m.