Triple

T11365131
Position Surface form Disambiguated ID Type / Status
Subject Taipei–Seoul E269182 entity
Predicate connectsCapitalCity P35272 FINISHED
Object Taipei E14412 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: Taipei | Statement: [Taipei–Seoul, connectsCapitalCity, Taipei]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taipei
Context triple: [Taipei–Seoul, connectsCapitalCity, Taipei]
  • A. Taipei, Taiwan chosen
    Taipei, Taiwan is the capital and largest city of Taiwan, known as a major political, economic, and cultural center in East Asia.
  • 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. 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.
  • D. Kaohsiung
    Kaohsiung is a major port city in southern Taiwan known for its heavy industry, modern harborfront, and growing cultural and arts scene.
  • E. Keelung
    Keelung is a major port city in northeastern Taiwan known for its busy harbor, seafood markets, and coastal scenery.
  • 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_69d6aacca1048190b39dbbc2174616fa completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea4589908190948a8225768e1eec completed April 9, 2026, 6:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5b7ee695c8190851ee2adb3e38738 completed April 20, 2026, 5:21 a.m.
Created at: April 8, 2026, 9:33 p.m.