Triple

T3108579
Position Surface form Disambiguated ID Type / Status
Subject Santa Isabel Island E64894 entity
Predicate languageSpoken P151 FINISHED
Object Kokota E146929 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 | Statement: [Santa Isabel Island, languageSpoken, Kokota]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kokota
Context triple: [Santa Isabel Island, languageSpoken, Kokota]
  • A. Kokota chosen
    Kokota is an Oceanic language spoken in the Solomon Islands, particularly on Santa Isabel Island.
  • B. Kota
    Kota is a major industrial and educational city in southeastern Rajasthan, India, known for its coaching institutes and power plants along the Chambal River.
  • C. Uji City
    Uji City is a historic city in Kyoto Prefecture, Japan, renowned for its high-quality green tea production and UNESCO-listed Byōdō-in Temple.
  • D. KOTA
    KOTA is a Timorese political party that participated in the resistance movement against Indonesian occupation and later in East Timor’s post-independence politics.
  • E. Namba City
    Namba City is a large shopping and entertainment complex in Osaka’s Namba district, featuring retail stores, restaurants, offices, and a rooftop garden integrated with the surrounding urban landscape.
  • 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_69ad857eeaf48190b34ebfdaa7a264cf completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada29eacc88190a19c5ca8e53e3dca completed March 8, 2026, 4:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69b203902a6881909b20589fad629640 completed March 12, 2026, 12:06 a.m.
Created at: March 8, 2026, 3:04 p.m.