Triple

T15642881
Position Surface form Disambiguated ID Type / Status
Subject National Freeway 1 E376109 entity
Predicate connects P390 FINISHED
Object Taoyuan 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: Taoyuan | Statement: [National Freeway 1, connects, Taoyuan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taoyuan
Context triple: [National Freeway 1, connects, 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. Taoyuan Xiang
    Taoyuan Xiang is a regional variety of the Xiang Chinese language spoken primarily in the Taoyuan area of Hunan Province, China.
  • E. Xinyi
    Xinyi is a county-level city administered by Maoming in Guangdong Province, China, known for its agriculture and regional commerce.
  • 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_69d85cd035a48190b73d5579ab73969a completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04ed23d688190bea996f90989d406 completed April 16, 2026, 2:52 a.m.
Created at: April 10, 2026, 4:15 a.m.