Triple

T20905610
Position Surface form Disambiguated ID Type / Status
Subject Gaegyeong E514789 entity
Predicate successor P78 FINISHED
Object Hanyang 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: Hanyang | Statement: [Gaegyeong, successor, Hanyang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanyang
Context triple: [Gaegyeong, successor, Hanyang]
  • A. Hanyang
    Hanyang is a historic district and former city now incorporated into Wuhan in Hubei Province, China, known for its early industrial development and strategic location at the confluence of the Han and Yangtze rivers.
  • B. Hejin
    Hejin is a county-level city in southern Shanxi Province, China, situated along the Fen River near its confluence with the Yellow River.
  • C. Hanseong chosen
    Hanseong was the historical name for Seoul when it served as the capital of the Joseon Dynasty in Korea.
  • D. Hamhung
    Hamhung is a major city in northeastern North Korea, known as an important industrial center and for its distinctive style of cold noodle dish, Hamhung naengmyeon.
  • E. Xintai
    Xintai is a county-level city in Shandong Province, China, administered by the prefecture-level city of Tai'an.
  • 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_69e0b4f8a1108190bce3d31331290ced completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6e8ff36488190987ecdfcbed4220c completed April 21, 2026, 3:03 a.m.
Created at: April 16, 2026, 12:47 p.m.