Triple

T16386148
Position Surface form Disambiguated ID Type / Status
Subject Shiding District E397926 entity
Predicate borderedBy P224 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: [Shiding District, borderedBy, Yilan County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yilan County
Context triple: [Shiding District, borderedBy, 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_69d87f2880b48190ae1a9673a3bbef80 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e3263d260081909db9ac6016d5738a completed April 18, 2026, 6:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00dbf46cf881909f6c16f7a3d9a535 completed May 10, 2026, 7:26 p.m.
Created at: April 10, 2026, 5:08 a.m.