Triple

T7128907
Position Surface form Disambiguated ID Type / Status
Subject Ongjin County E166135 entity
Predicate capital P234 FINISHED
Object Ongjin-eup
Ongjin-eup is the main town and administrative center of Ongjin County in North Korea’s South Hwanghae Province.
E652799 NE FINISHED

How this triple was built (4 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: Ongjin-eup | Statement: [Ongjin County, capital, Ongjin-eup]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ongjin-eup
Context triple: [Ongjin County, capital, Ongjin-eup]
  • A. Eonyang-eup
    Eonyang-eup is a town in Ulju County, Ulsan, South Korea, known as a local administrative and commercial hub for the surrounding region.
  • B. Geumwang-eup
    Geumwang-eup is a town-level administrative division in Eumseong County, located in North Chungcheong Province, South Korea.
  • C. Ungchon-myeon
    Ungchon-myeon is a rural township-level administrative division located within Ulju County in Ulsan, South Korea.
  • D. Eumseong-eup
    Eumseong-eup is the main urban township and administrative center of Eumseong County in North Chungcheong Province, South Korea.
  • E. Suyŏng-gu
    Suyŏng-gu is an urban district of Busan, South Korea, known for its coastal location and role as a residential and commercial hub within the city.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ongjin-eup
Triple: [Ongjin County, capital, Ongjin-eup]
Generated description
Ongjin-eup is the main town and administrative center of Ongjin County in North Korea’s South Hwanghae Province.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ongjin-eup
Target entity description: Ongjin-eup is the main town and administrative center of Ongjin County in North Korea’s South Hwanghae Province.
  • A. Eonyang-eup
    Eonyang-eup is a town in Ulju County, Ulsan, South Korea, known as a local administrative and commercial hub for the surrounding region.
  • B. Geumwang-eup
    Geumwang-eup is a town-level administrative division in Eumseong County, located in North Chungcheong Province, South Korea.
  • C. Ungchon-myeon
    Ungchon-myeon is a rural township-level administrative division located within Ulju County in Ulsan, South Korea.
  • D. Eumseong-eup
    Eumseong-eup is the main urban township and administrative center of Eumseong County in North Chungcheong Province, South Korea.
  • E. Suyŏng-gu
    Suyŏng-gu is an urban district of Busan, South Korea, known for its coastal location and role as a residential and commercial hub within the city.
  • F. None of above. chosen

Provenance (5 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_69c6888350588190870cd552b427a1cd completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e66c87848190b0ffd08e3c3f4877 completed March 27, 2026, 8:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7daff33bc8190825078d791ff0b3a completed March 28, 2026, 1:43 p.m.
NEDg Description generation batch_69c7db989e548190b6f41e62b17a63cb completed March 28, 2026, 1:46 p.m.
NED2 Entity disambiguation (via description) batch_69c7dc06d7808190906b7f710e7d9843 completed March 28, 2026, 1:47 p.m.
Created at: March 27, 2026, 2:44 p.m.