Triple

T23408021
Position Surface form Disambiguated ID Type / Status
Subject Hamhung E559987 entity
Predicate nearbyCity P350 FINISHED
Object Hungnam 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: Hungnam | Statement: [Hamhung, nearbyCity, Hungnam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hungnam
Context triple: [Hamhung, nearbyCity, Hungnam]
  • A. Hungnam chosen
    Hungnam is a port city on North Korea’s east coast that served as a major industrial center and the site of a large-scale UN evacuation during the Korean War.
  • B. Yŏngnŭng
    Yŏngnŭng is the McCune–Reischauer romanization of Yeongneung, a royal tomb site in Paju, South Korea.
  • C. Phyongwon
    Phyongwon is a city in North Korea known as an administrative and agricultural center within North Pyongan Province.
  • D. Pak Hyŏkkŏse
    Pak Hyŏkkŏse is the legendary founding monarch of the ancient Korean kingdom of Silla, traditionally said to have established the state in 57 BCE.
  • E. Ungjin
    Ungjin was an ancient city in the Korean kingdom of Baekje that served as one of its historical capitals and a key political and cultural center.
  • 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_69e2454b3a5881909c64773dc8a5d289 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1a50f3f90819084fb682597fee1e1 completed April 29, 2026, 6:28 a.m.
Created at: April 17, 2026, 5:38 p.m.