Triple

T16360366
Position Surface form Disambiguated ID Type / Status
Subject Incheon E397293 entity
Predicate hasDistrict P459 FINISHED
Object Jung District E152773 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: Jung District | Statement: [Incheon, hasDistrict, Jung District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jung District
Context triple: [Incheon, hasDistrict, Jung District]
  • A. Jung District
    Jung District is a central administrative and commercial district in Seoul, South Korea, known for its major business centers, historic sites, and cultural landmarks.
  • B. Jung District
    Jung District is a central administrative and commercial district of Busan, South Korea, known for its historic markets, port-side location, and dense urban landscape.
  • C. Jung District chosen
    Jung District is a central coastal district of Incheon, South Korea, known for encompassing Incheon International Airport and parts of the city’s historic port area.
  • D. Kang District
    Kang District is an administrative district located in Nimruz Province in southwestern Afghanistan.
  • E. Sanchong District
    Sanchong District is a densely populated urban district in New Taipei City, Taiwan, situated across the river from central Taipei and known for its residential neighborhoods and commercial activity.
  • 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_69d87f2778dc8190aa95c7572db127e6 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2fad241848190a9f32c7b050f20a5 completed April 18, 2026, 3:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00580fec0c8190b7fb73dbc637fb61 completed May 10, 2026, 10:04 a.m.
Created at: April 10, 2026, 5:08 a.m.