Triple

T7213990
Position Surface form Disambiguated ID Type / Status
Subject Kavalan language E149481 entity
Predicate region P40 FINISHED
Object Yilan County E376097 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: Yilan County | Statement: [Kavalan language, region, Yilan County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yilan County
Context triple: [Kavalan language, region, Yilan County]
  • A. Yilan County chosen
    Yilan County is a scenic coastal county in northeastern Taiwan known for its mountains, hot springs, and cultural festivals.
  • B. Hualien County
    Hualien County is a largely mountainous and coastal county on Taiwan’s eastern shore, known for its dramatic Pacific coastline and the famous Taroko Gorge.
  • C. Yunlin County
    Yunlin County is a largely rural county in western Taiwan known for its extensive agricultural production and traditional cultural heritage.
  • D. Ping-tung County
    Ping-tung County is a largely rural county at the southern tip of Taiwan, known for its tropical climate, coastal scenery, and attractions such as Kenting National Park.
  • E. Taitung County
    Taitung County is a largely rural coastal county in southeastern Taiwan known for its indigenous cultures, scenic Pacific coastline, and relatively low level of urban development.
  • 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_69c687eca814819095abb52316b1af80 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6e98cbebc8190941e76259c988790 completed March 27, 2026, 8:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7d381a7288190bbfdb8f1de6b5f05 completed March 28, 2026, 1:11 p.m.
Created at: March 27, 2026, 2:53 p.m.