Triple

T15476610
Position Surface form Disambiguated ID Type / Status
Subject Hsinchu–Taipei–Keelung corridor E376795 entity
Predicate containsCity P294 FINISHED
Object Hsinchu E198701 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: Hsinchu | Statement: [Hsinchu–Taipei–Keelung corridor, containsCity, Hsinchu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hsinchu
Context triple: [Hsinchu–Taipei–Keelung corridor, containsCity, Hsinchu]
  • A. Hsinchu, Taiwan chosen
    Hsinchu, Taiwan is a major high-tech city often called Taiwan’s “Silicon Valley,” known for its science park and concentration of semiconductor and electronics companies.
  • B. Taichung
    Taichung is a major city in central Taiwan known for its cultural attractions, mild climate, and role as an important economic and transportation hub.
  • C. Tainan
    Tainan is a historic city in southern Taiwan known for its well-preserved temples, traditional culture, and status as the island’s former capital.
  • D. Xinyi
    Xinyi is a county-level city administered by Maoming in Guangdong Province, China, known for its agriculture and regional commerce.
  • E. Xinyi
    Xinyi is a county-level city administered by Xuzhou in Jiangsu Province, eastern China.
  • 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_69d85cd21dcc81908646251b1c26ea00 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f88a5dc8190a2d7830748e29180 completed April 16, 2026, 1:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a002d966ffc8190aa0d9d3abf8ad593 completed May 10, 2026, 7:02 a.m.
Created at: April 10, 2026, 3:34 a.m.