Triple

T21301122
Position Surface form Disambiguated ID Type / Status
Subject Hau Pei-tsun E525063 entity
Predicate residence P75 FINISHED
Object Taipei, Taiwan NE NERFINISHED

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, Taiwan | Statement: [Hau Pei-tsun, residence, Taipei, Taiwan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taipei, Taiwan
Context triple: [Hau Pei-tsun, residence, Taipei, Taiwan]
  • 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. Chiayi City, Taiwan
    Chiayi City, Taiwan, is a historic city in southwestern Taiwan known as a gateway to Alishan and for its rich cultural heritage and traditional night markets.
  • C. Hsinchu, Taiwan
    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.
  • D. 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.
  • E. Songshan District, Taipei, Taiwan
    Songshan District is a bustling urban area in eastern Taipei, Taiwan, known for its mix of traditional markets, modern commercial centers, and riverside parks.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b517e6748190850d6f6ddf323d69 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7385c078881908a451be1a19a64c5 completed April 21, 2026, 8:42 a.m.
Created at: April 16, 2026, 4:05 p.m.