Triple

T5691302
Position Surface form Disambiguated ID Type / Status
Subject Seediq E125432 entity
Predicate traditionalRegion P1968 FINISHED
Object Hualien County E557672 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: Hualien County | Statement: [Seediq, traditionalRegion, Hualien County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hualien County
Context triple: [Seediq, traditionalRegion, Hualien County]
  • A. Hualien County chosen
    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.
  • B. 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.
  • C. Yilan County
    Yilan County is a scenic coastal county in northeastern Taiwan known for its mountains, hot springs, and cultural festivals.
  • D. Yunlin County
    Yunlin County is a largely rural county in western Taiwan known for its extensive agricultural production and traditional cultural heritage.
  • E. Chiayi County
    Chiayi County is a largely rural county in southwestern Taiwan known for its agriculture, cultural attractions, and proximity to scenic areas such as Alishan.
  • 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_69c0082bb19c8190823a4facd3cba79b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c023e500ec8190bfda4f6a818aa5dc completed March 22, 2026, 5:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1133b6ce0819080ec5d6bad6d2e97 completed March 23, 2026, 10:17 a.m.
Created at: March 22, 2026, 3:44 p.m.