Triple

T5593180
Position Surface form Disambiguated ID Type / Status
Subject Kokota E146929 entity
Predicate hasAlternativeName P39 FINISHED
Object Kokota language E155832 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: Kokota language | Statement: [Kokota, hasAlternativeName, Kokota language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kokota language
Context triple: [Kokota, hasAlternativeName, Kokota language]
  • A. Kokota language chosen
    The Kokota language is an Austronesian language spoken by the Kokota people of Santa Isabel Island in the Solomon Islands.
  • B. Kioko language
    The Kioko language is an Austronesian language of the Muna–Buton subgroup spoken by a small community in southeastern Sulawesi, Indonesia.
  • C. Konkow language
    The Konkow language is an endangered Native American language traditionally spoken by the Konkow (Koyom’kawi) people of northern California.
  • D. Koya language
    Koya language is a South-Central Dravidian language spoken by the Koya tribal communities in central and southern India.
  • E. Kaado language
    The Kaado language is a regional variety within the Songhay language family spoken by communities in parts of West Africa.
  • 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_69c009036c408190981a8d690b679b67 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c020bb08648190ab1f66cc3e897e6d completed March 22, 2026, 5:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0286b4d2c8190a3224f3082316dc8 completed March 22, 2026, 5:35 p.m.
Created at: March 22, 2026, 3:38 p.m.