Triple

T14241508
Position Surface form Disambiguated ID Type / Status
Subject Gwanak-gu E353016 entity
Predicate hasNeighbour P5707 FINISHED
Object Dongjak-gu E613688 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: Dongjak-gu | Statement: [Gwanak-gu, hasNeighbour, Dongjak-gu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dongjak-gu
Context triple: [Gwanak-gu, hasNeighbour, Dongjak-gu]
  • A. Dongjak District chosen
    Dongjak District is a residential and administrative district in southern Seoul, South Korea, known for its riverside parks along the Han River and major transportation hubs.
  • B. Chongno-gu
    Chongno-gu is a central district in Seoul, South Korea, known as the historic and cultural heart of the city, home to major palaces, government institutions, and traditional markets.
  • C. Gangseo-gu
    Gangseo-gu is a western coastal district of Busan, South Korea, known for its industrial complexes, logistics hubs, and proximity to Gimhae International Airport.
  • D. Seongbuk-gu
    Seongbuk-gu is a district in northern Seoul, South Korea, known for its residential neighborhoods, cultural sites, and several major universities.
  • E. Jung-gu
    Jung-gu is a central district of the metropolitan city of Daejeon in South Korea, known for its mix of commercial, residential, and administrative areas.
  • 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_69d8278adc7c8190a9218d69bce3c4e6 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6244ad188190b9d9db7914240410 completed April 14, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd949df6688190ac92f7e0945bce02 completed May 8, 2026, 7:45 a.m.
Created at: April 10, 2026, 1:08 a.m.