Triple

T20249361
Position Surface form Disambiguated ID Type / Status
Subject Coapa area E498508 entity
Predicate contains P35 FINISHED
Object Villa Coapa NE NERFINISHED

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: Villa Coapa | Statement: [Coapa area, contains, Villa Coapa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Villa Coapa
Context triple: [Coapa area, contains, Villa Coapa]
  • A. Villa Coapa chosen
    Villa Coapa is a residential and commercial neighborhood in southern Mexico City known for its shopping centers, schools, and middle-class housing.
  • B. Villa Madero
    Villa Madero is a residential locality within the Greater Buenos Aires metropolitan area in Argentina, known for its urban character and proximity to the city of Buenos Aires.
  • C. Villa Hidalgo
    Villa Hidalgo is a municipality and town in the Los Altos region of Jalisco, Mexico, known for its agricultural traditions and regional commerce.
  • D. Villa Cisneros
    Villa Cisneros, now known as Dakhla, is a coastal city in Western Sahara that historically served as a key Spanish colonial outpost and administrative hub.
  • E. Villa El Carmen
    Villa El Carmen is a municipality in western Nicaragua known for its rural communities and agricultural activities within the Managua department.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da6274c58c81909c646eabed6f4f30 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e673a699b48190a2073a3bd8851125 completed April 20, 2026, 6:42 p.m.
Created at: April 11, 2026, 11:41 p.m.