Triple

T15067382
Position Surface form Disambiguated ID Type / Status
Subject Taiwan Railways network E379789 entity
Predicate connects P390 FINISHED
Object Changhua E551628 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: Changhua | Statement: [Taiwan Railways network, connects, Changhua]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Changhua
Context triple: [Taiwan Railways network, connects, Changhua]
  • A. Changhua County chosen
    Changhua County is a largely agricultural and coastal county in central-western Taiwan, known for its fertile plains, historic temples, and dense population.
  • B. Nantou
    Nantou is a historic subdistrict in Shenzhen’s Nanshan District, known as the site of the old county seat and a preserved ancient town area.
  • C. Chiayi County
    Chiayi County is a largely rural county in southwestern Taiwan known for its agriculture, cultural attractions, and proximity to scenic areas such as Alishan.
  • D. Nantou County
    Nantou County is a mountainous county in central Taiwan known for its indigenous communities, scenic landscapes like Sun Moon Lake, and its role in significant historical events.
  • E. Yuanlin
    Yuanlin is a township-level city in Changhua County, central Taiwan, known as a regional commercial and transportation hub.
  • 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_69fec878c52c8190bf010b1fd4d21f65 completed May 9, 2026, 5:39 a.m.
Created at: April 10, 2026, 3:02 a.m.