Triple

T598339
Position Surface form Disambiguated ID Type / Status
Subject Kiliwa language E11436 entity
Predicate spokenIn P2266 FINISHED
Object Mexico E346 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: Mexico | Statement: [Kiliwa language, spokenIn, Mexico]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mexico
Context triple: [Kiliwa language, spokenIn, Mexico]
  • A. Mexico chosen
    Mexico is a large North American country known for its rich pre-Columbian and colonial history, diverse cultures, and influential cuisine and arts.
  • B. State of Mexico
    The State of Mexico is a populous federal entity in central Mexico that surrounds much of Mexico City and is a major political, economic, and industrial hub of the country.
  • C. MEX
    MEX is the IATA airport code for Mexico City International Airport, the main international gateway serving Mexico City and one of the busiest airports in Latin America.
  • D. Guatemala
    Guatemala is a Central American country known for its Mayan heritage, volcanic landscapes, and vibrant indigenous cultures.
  • E. southern Mexico
    Southern Mexico is a culturally diverse and geographically varied region of Mexico known for its mountainous terrain, indigenous communities, and important archaeological and ecological sites.
  • 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_69a4932779b881908688590d59c71900 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49d776c6c819081b41a9b55041cd5 completed March 1, 2026, 8:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69a55544eda481908fae6a9f77ff9d97 completed March 2, 2026, 9:15 a.m.
Created at: March 1, 2026, 7:35 p.m.