Triple

T6160134
Position Surface form Disambiguated ID Type / Status
Subject Banggai language E137418 entity
Predicate glottologName P6521 FINISHED
Object Banggai E384826 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: Banggai | Statement: [Banggai language, glottologName, Banggai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Banggai
Context triple: [Banggai language, glottologName, Banggai]
  • A. Banggai chosen
    Banggai is a coastal town and regency seat in Indonesia known for its location in the Banggai Islands off the eastern coast of Central Sulawesi.
  • B. Bantia
    Bantia was an ancient Oscan-speaking city in southern Italy, notable for yielding important inscriptions that illuminate the Oscan language and Italic legal traditions.
  • C. Kainan
    Kainan is a coastal city in central Wakayama Prefecture, Japan, known for its traditional industries and scenic seaside setting.
  • D. Gaya Island
    Gaya Island is a forested tropical island off the coast of Sabah, Malaysia, known for its beaches, coral reefs, and inclusion in the Tunku Abdul Rahman Marine Park.
  • E. Biliran Island
    Biliran Island is a small island province in the Eastern Visayas region of the Philippines known for its coastal landscapes, waterfalls, and predominantly Waray-speaking population.
  • 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_69c008a54fc88190b6ce4416490ca79d completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05d3445dc8190822954cee90f0dd7 completed March 22, 2026, 9:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c14194d31081908e61a867f11117b4 completed March 23, 2026, 1:35 p.m.
Created at: March 22, 2026, 4:17 p.m.