Triple

T7656683
Position Surface form Disambiguated ID Type / Status
Subject Gela E173401 entity
Predicate hasNeighbouringLanguage P16383 FINISHED
Object Bugotu E147942 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: Bugotu | Statement: [Gela, hasNeighbouringLanguage, Bugotu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bugotu
Context triple: [Gela, hasNeighbouringLanguage, Bugotu]
  • A. Bugotu chosen
    Bugotu is an Austronesian language of the Meso-Melanesian subgroup spoken primarily on Santa Isabel Island in the Solomon Islands.
  • B. Tabonibara
    Tabonibara is a village located on the atoll of Butaritari in the island nation of Kiribati in the central Pacific Ocean.
  • C. Kibushi
    Kibushi is a Bantu language spoken primarily in Mayotte, where it serves as one of the island’s main regional languages.
  • D. Ogakumonjo
    Ogakumonjo is a historic structure within Kyoto Imperial Palace, traditionally associated with imperial academic or archival functions in Japan’s former capital.
  • E. Honancho
    Honancho is a neighborhood in Tokyo, Japan, known as a residential area with convenient access to central city districts via the Tokyo Metro Marunouchi Line.
  • 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_69c69955517c819085bc715b96d304d2 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7018fcbb48190a479f2effd939a8e completed March 27, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c89b05846c8190b49540aeae43dd9a completed March 29, 2026, 3:22 a.m.
Created at: March 27, 2026, 3:59 p.m.