Triple

T16025038
Position Surface form Disambiguated ID Type / Status
Subject Guatemala Department E388695 entity
Predicate contains P35 FINISHED
Object Chinautla E492382 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: Chinautla | Statement: [Guatemala Department, contains, Chinautla]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chinautla
Context triple: [Guatemala Department, contains, Chinautla]
  • A. Chinautla chosen
    Chinautla is a municipality in Guatemala known for its significant Poqomam Maya population and preservation of indigenous cultural traditions.
  • B. Chino
    Chino is a city in Southern California known for its agricultural roots, suburban communities, and proximity to major Inland Empire transportation corridors.
  • C. Chicanná
    Chicanná is a small Maya archaeological site in the Mexican state of Campeche, noted for its well-preserved temples and elaborate zoomorphic façades.
  • D. Chepe
    Chepe is a masculine given name and nickname, commonly used in Spanish-speaking regions as a familiar form of names like José.
  • E. Chepe
    Chepe is a scenic Mexican passenger train service that runs through the Copper Canyon region in the state of Chihuahua.
  • 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_69d86dada3808190825d5f80d72fbe88 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1832790548190a74045d554e13328 completed April 17, 2026, 12:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffcf31c8d8819096c562ba1453f3c0 completed May 10, 2026, 12:20 a.m.
Created at: April 10, 2026, 4:55 a.m.