Triple

T6561697
Position Surface form Disambiguated ID Type / Status
Subject Jakaltek E153797 entity
Predicate closelyRelatedTo P37 FINISHED
Object Akateko E411186 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: Akateko | Statement: [Jakaltek, closelyRelatedTo, Akateko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Akateko
Context triple: [Jakaltek, closelyRelatedTo, Akateko]
  • A. Akateko chosen
    Akateko is a Mayan language spoken primarily by the Akateko people in the western highlands of Guatemala and parts of southern Mexico.
  • B. Aku Uka
    Aku Uka is the paramount traditional monarch of the Jukun people, historically associated with the ancient Kwararafa kingdom in present-day Taraba State, Nigeria.
  • C. Agutaynen
    Agutaynen is an Austronesian language spoken by the Agutaynen people in the Philippines, primarily in the province of Palawan.
  • D. Aku Aku
    Aku Aku is a sentient wooden mask who guides and protects Crash Bandicoot throughout the Crash Bandicoot video game series.
  • E. Akoko
    Akoko is a prominent Yoruba sub-ethnic group in southwestern Nigeria, primarily inhabiting the northeastern part of Ondo State and parts of neighboring states.
  • 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_69c6880cb35881909b763eb0125236b9 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ae38e94081908f964d130f9147d8 completed March 27, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d55fa1bc81908f2929e835051532 completed March 27, 2026, 7:07 p.m.
Created at: March 27, 2026, 1:52 p.m.