Triple

T7325905
Position Surface form Disambiguated ID Type / Status
Subject Taoyuan Leopards E168874 entity
Predicate basedIn P40 FINISHED
Object Taoyuan E159989 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: Taoyuan | Statement: [Taoyuan Leopards, basedIn, Taoyuan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taoyuan
Context triple: [Taoyuan Leopards, basedIn, Taoyuan]
  • A. Taoyuan City chosen
    Taoyuan City is a major municipality in northwestern Taiwan known for its rapidly growing urban areas, industrial zones, and proximity to Taiwan Taoyuan International Airport.
  • B. Taoyuan District
    Taoyuan District is the central urban and administrative hub of Taoyuan City in northwestern Taiwan, known for its dense population, commercial activity, and transportation links.
  • 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. Xinyi
    Xinyi is a county-level city administered by Xuzhou in Jiangsu Province, eastern China.
  • E. 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.
  • 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_69c68a54cacc81908e3b773441f19566 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f0a612c08190b7a3fefa811bbcec completed March 27, 2026, 9:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69c9493bf8088190bc59dd0e36d16a20 completed March 29, 2026, 3:46 p.m.
Created at: March 27, 2026, 3:03 p.m.