Triple

T15067386
Position Surface form Disambiguated ID Type / Status
Subject Taiwan Railways network E379789 entity
Predicate connects P390 FINISHED
Object Kaohsiung E151217 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: Kaohsiung | Statement: [Taiwan Railways network, connects, Kaohsiung]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kaohsiung
Context triple: [Taiwan Railways network, connects, Kaohsiung]
  • A. Kaohsiung chosen
    Kaohsiung is a major port city in southern Taiwan known for its heavy industry, modern harborfront, and growing cultural and arts scene.
  • B. 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.
  • C. Keelung
    Keelung is a major port city in northeastern Taiwan known for its busy harbor, seafood markets, and coastal scenery.
  • D. Pingtung City
    Pingtung City is an urban center in southern Taiwan known as the political and economic hub of Pingtung County.
  • E. Tainan metropolitan area
    The Tainan metropolitan area is a major urban region in southern Taiwan centered on the historic city of Tainan and its surrounding districts.
  • 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_69d85cd7683881908d405c1b5d7b4f7f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69dedeea750c819082d8823c9ab6c5a2 completed April 15, 2026, 12:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffeb7921208190bbf4e1a01c6ec5ee completed May 10, 2026, 2:20 a.m.
Created at: April 10, 2026, 3:02 a.m.