Triple

T2048788
Position Surface form Disambiguated ID Type / Status
Subject State of Guanajuato E45514 entity
Predicate hasMunicipality P847 FINISHED
Object Silao E63068 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: Silao | Statement: [State of Guanajuato, hasMunicipality, Silao]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Silao
Context triple: [State of Guanajuato, hasMunicipality, Silao]
  • A. Malpaso
    Malpaso is the highest peak on the Canary Island of El Hierro, known for its panoramic views over the island and surrounding Atlantic Ocean.
  • B. Silao Municipality chosen
    Silao Municipality is an administrative region in the state of Guanajuato, Mexico, known for its industrial activity and proximity to the city of León and the Bajío industrial corridor.
  • C. Los Baños
    Los Baños is a municipality in the Philippines known as a major center for agricultural research and education, particularly in rice science.
  • D. Kapyong
    Kapyong is a Korean War battlefield in South Korea renowned for a pivotal 1951 engagement in which outnumbered UN forces, including Canadian troops, halted a major Chinese offensive.
  • E. Sibaté
    Sibaté is a municipality in central Colombia known for its agricultural production and proximity to Bogotá within the Cundinamarca Department.
  • 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_69a8891948208190ab7898da21824c77 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb98c70c48190beb98aad56d9daf1 completed March 7, 2026, 5:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae2007386481908b46c7bc2db8e4dd completed March 9, 2026, 1:19 a.m.
Created at: March 4, 2026, 7:39 p.m.