Triple

T10930849
Position Surface form Disambiguated ID Type / Status
Subject Colonia Asturias E258200 entity
Predicate adjacentTo P224 FINISHED
Object Colonia Tránsito E50660 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: Colonia Tránsito | Statement: [Colonia Asturias, adjacentTo, Colonia Tránsito]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Colonia Tránsito
Context triple: [Colonia Asturias, adjacentTo, Colonia Tránsito]
  • A. Colonia Tránsito chosen
    Colonia Tránsito is a neighborhood in central Mexico City located within the Cuauhtémoc borough, known for its urban residential character and proximity to the historic downtown area.
  • B. Colonia
    Colonia is the main administrative and population center of Yap State in the Federated States of Micronesia, located on the island of Yap.
  • C. Colonia
    Colonia is the historical Latin name for the German city of Cologne, reflecting its origins as a Roman colony.
  • D. Colonia Doctores
    Colonia Doctores is a traditional central neighborhood in Mexico City known for its historic streets, mixed residential and commercial character, and proximity to major civic and cultural institutions.
  • E. Colonia Jardín
    Colonia Jardín is a transport hub and neighborhood in Madrid, Spain, known for its metro and light rail connections linking the city with nearby suburbs.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7709f92088190a15ae3638d3b14fb completed April 9, 2026, 9:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2d710f65c8190a4ef17a6d90a19d2 completed April 18, 2026, 12:57 a.m.
Created at: April 8, 2026, 9:22 p.m.