Triple

T21721066
Position Surface form Disambiguated ID Type / Status
Subject Seoul Subway Line 1 E536155 entity
Predicate connects P390 FINISHED
Object Anyang 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: Anyang | Statement: [Seoul Subway Line 1, connects, Anyang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anyang
Context triple: [Seoul Subway Line 1, connects, Anyang]
  • A. Anyang
    Anyang is an ancient city in northern China renowned as one of the historical capitals of the Shang dynasty and a major archaeological site.
  • B. Anyang chosen
    Anyang is a mid-sized South Korean city in the Seoul Capital Area known for its residential districts, light industry, and proximity to central Seoul.
  • C. Sanhe City
    Sanhe City is a county-level city in Hebei Province, China, located near Beijing and forming part of the Beijing–Tianjin–Hebei metropolitan region.
  • D. Taian
    Taian is a prefecture-level city in eastern China's Shandong province, best known as the gateway to the sacred Mount Tai.
  • E. Hejin
    Hejin is a county-level city in southern Shanxi Province, China, situated along the Fen River near its confluence with the Yellow River.
  • 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_69e0c46c6dd88190a595375fa6ebd701 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69efd96f1fbc8190a202f834aec1a319 completed April 27, 2026, 9:47 p.m.
Created at: April 16, 2026, 6:47 p.m.