Triple

T31438151
Position Surface form Disambiguated ID Type / Status
Subject Gyeonggi Provincial Government E801990 entity
Predicate governsAreaAround P49097 FINISHED
Object Seoul 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: Seoul | Statement: [Gyeonggi Provincial Government, governsAreaAround, Seoul]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: governsAreaAround
Context triple: [Gyeonggi Provincial Government, governsAreaAround, Seoul]
  • A. governanceArea
    Indicates the geographic or jurisdictional area over which an entity has governing authority or responsibility.
  • B. governsAreaKnownFor
    Indicates that a governing entity exercises authority over an area that is notably recognized for a particular characteristic, feature, or attribute.
  • C. governedNear
    Indicates that one entity exercises governing authority over an area or entity that is geographically close to another specified entity or location.
  • D. coreTerritoryAround
    Indicates that one entity serves as the central or primary territory surrounding or enclosing another entity.
  • E. areaOfAuthority chosen
    Indicates the domain, region, or scope within which an entity has official power, control, or responsibility.
  • F. None of above.

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_69f348c475348190bf579ca858eec77c completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69ffdd05d1908190957deb11392f4595 completed May 10, 2026, 1:19 a.m.
PD Predicate disambiguation batch_69ffdc0d33c881908b3483bee8a96540 completed May 10, 2026, 1:14 a.m.
Created at: April 30, 2026, 9:03 p.m.