Triple

T11856605
Position Surface form Disambiguated ID Type / Status
Subject Martín Carrera E282055 entity
Predicate hasStationCode P1289 FINISHED
Object CA
CA is the station code assigned to the Martín Carrera transit station in Mexico City’s public transportation system.
E949104 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: CA | Statement: [Martín Carrera, hasStationCode, CA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CA
Context triple: [Martín Carrera, hasStationCode, CA]
  • A. CA
    CA is the two-letter U.S. postal abbreviation for the state of California.
  • B. CA
    CA is the commonly used abbreviation for Club Africain, a major Tunisian multi-sport club best known for its football team based in Tunis.
  • C. CA
    CA is the commonly used abbreviation for the Court of Appeals of the Philippines, the country's second-highest judicial body that reviews decisions of lower courts and quasi-judicial agencies.
  • D. CA
    CA is the official abbreviation used for the professional head of the Australian Army.
  • E. CA
    CA is the postcode area covering Carlisle and surrounding parts of Cumbria in north-west England.
  • 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: CA
Triple: [Martín Carrera, hasStationCode, CA]
Generated description
CA is the station code assigned to the Martín Carrera transit station in Mexico City’s public transportation system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: CA
Target entity description: CA is the station code assigned to the Martín Carrera transit station in Mexico City’s public transportation system.
  • A. CA
    CA is the vehicle registration code used on license plates for the Italian city of Cagliari.
  • B. CA
    CA is the two-letter U.S. postal abbreviation for the state of California.
  • C. CA
    CA is the IATA airline designator assigned to Air China, the flag carrier of the People's Republic of China.
  • D. CA
    CA is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Canada in international standards and systems.
  • E. CA
    CA is the abbreviated name for the Council of Administration, one of the main governing bodies of the Universal Postal Union responsible for overseeing its operations and policy implementation.
  • 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_69d6ab287ba48190a5178779fd19b9b7 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a699089c8190b7a298baf13dcded completed April 10, 2026, 7:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69f167d9b9e8819093582637941fc5ca completed April 29, 2026, 2:07 a.m.
NEDg Description generation batch_69f17006e6108190b51b20ddf6d2368c completed April 29, 2026, 2:42 a.m.
NED2 Entity disambiguation (via description) batch_69f17819af5c8190a98db3cd8eff8da2 completed April 29, 2026, 3:16 a.m.
Created at: April 8, 2026, 9:43 p.m.