Triple

T13876444
Position Surface form Disambiguated ID Type / Status
Subject Colima E333594 entity
Predicate hasMunicipality P847 FINISHED
Object Comala E876947 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: Comala | Statement: [Colima, hasMunicipality, Comala]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Comala
Context triple: [Colima, hasMunicipality, Comala]
  • A. Comala chosen
    Comala is the haunting, ghostly Mexican town that serves as the central setting of Juan Rulfo’s novel "Pedro Páramo."
  • B. Melaque
    Melaque is a coastal town in Jalisco, Mexico, known for its relaxed beach atmosphere, tourism, and role as a popular vacation spot on the Pacific coast.
  • C. Marcali
    Marcali is a small town in southwestern Hungary known for its agricultural surroundings and role as a local administrative and service center in Somogy County.
  • D. Donnacona
    Donnacona is a small town in the Capitale-Nationale region of Quebec, Canada, located west of Quebec City along the Saint Lawrence River.
  • E. Butambala
    Butambala is a county in the Buganda Kingdom of central Uganda, known for its predominantly rural communities and agricultural activities.
  • 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_69d81c5ced9c8190b0e9bcc6effe5959 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0be556708190bbcf0b3583f677e3 completed April 14, 2026, 9:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7ce6df2ac819089024b9ede7b205f completed May 3, 2026, 10:38 p.m.
Created at: April 9, 2026, 10:15 p.m.