Triple

T18991828
Position Surface form Disambiguated ID Type / Status
Subject Atsugewi language E464700 entity
Predicate hasAlternativeName P39 FINISHED
Object Atsuge 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: Atsuge | Statement: [Atsugewi language, hasAlternativeName, Atsuge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Atsuge
Context triple: [Atsugewi language, hasAlternativeName, Atsuge]
  • A. Atsugi
    Atsugi is a city in Kanagawa Prefecture, Japan, known as a regional commercial and industrial center with convenient access to the Tokyo metropolitan area.
  • B. Atsuma
    Atsuma is a small coastal town in Hokkaido, Japan, known for its rural landscape and proximity to the Pacific Ocean.
  • C. Asago
    Asago is a city in northern Hyōgo Prefecture, Japan, known for its mountainous scenery, historic castle ruins, and hot spring resorts.
  • D. Atsugewi chosen
    Atsugewi is a nearly extinct Native American language of the Palaihnihan family traditionally spoken in northeastern California.
  • E. Asaka
    Asaka is a Japanese noble family name historically associated with a collateral branch of the Imperial Family, including Prince Asaka Yasuhiko.
  • 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_69d8dd01a56c81909694a128c66b21d7 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d67dee4c8190ac2017ff748ea6aa completed April 20, 2026, 7:32 a.m.
Created at: April 10, 2026, 12:01 p.m.