Triple

T23060181
Position Surface form Disambiguated ID Type / Status
Subject Bunung E574275 entity
Predicate autonym P1435 FINISHED
Object Bunun NE NERFINISHED

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: Bunun | Statement: [Bunung, autonym, Bunun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bunun
Context triple: [Bunung, autonym, Bunun]
  • A. Bunun chosen
    The Bunun are an indigenous Austronesian people of Taiwan known for their rich oral traditions, polyphonic vocal music, and high-mountain agricultural lifestyle.
  • B. Bun
    Bun is a modern, high-performance JavaScript runtime and toolkit designed as an alternative to Node.js and Deno, featuring a built-in bundler, test runner, and package manager.
  • C. Buna
    Buna is the Nazi concentration and labor camp complex near Auschwitz where Elie Wiesel is imprisoned in his memoir "Night."
  • D. Buna
    Buna is a coastal village in Papua New Guinea that was a key site of intense fighting between Allied and Japanese forces during World War II’s New Guinea campaign.
  • E. Buna
    Buna is a short but significant karst river in Bosnia and Herzegovina, renowned for its powerful spring at Blagaj and its contribution to the Neretva river system.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245ba7ae48190be606dbc54120e39 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1899f359081909e89e19db3833a3d completed April 29, 2026, 4:31 a.m.
Created at: April 17, 2026, 3:55 p.m.