Triple

T4839102
Position Surface form Disambiguated ID Type / Status
Subject Gangnam District E108134 entity
Predicate locatedIn P40 FINISHED
Object Seoul Capital Area E166134 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: Seoul Capital Area | Statement: [Gangnam District, locatedIn, Seoul Capital Area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seoul Capital Area
Context triple: [Gangnam District, locatedIn, Seoul Capital Area]
  • A. Seoul Capital Area chosen
    The Seoul Capital Area is South Korea’s largest metropolitan region, encompassing Seoul, Incheon, and surrounding Gyeonggi Province, and serving as the country’s political, economic, and cultural hub.
  • B. Yongin
    Yongin is a rapidly growing city in the Seoul Capital Area of South Korea, known for attractions like Everland Resort and the Korean Folk Village.
  • C. Seoul
    Seoul is the capital and largest metropolis of South Korea, known as a major global center for technology, culture, and finance.
  • D. Incheon
    Incheon is a major port city in northwestern South Korea, known for its international airport and role as a key transportation and economic hub.
  • E. Uijeongbu
    Uijeongbu is a city in South Korea known as a suburban hub north of Seoul, featuring residential districts, commercial centers, and a history of hosting U.S. military bases.
  • 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_69bd43fbe444819085cb970706ef73f7 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6ce4a5108190aede620d5dde1f81 completed March 20, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69beb0cd44088190ba26171758898497 completed March 21, 2026, 2:53 p.m.
Created at: March 20, 2026, 1:25 p.m.