Triple

T1644745
Position Surface form Disambiguated ID Type / Status
Subject Gangseo District E35554 entity
Predicate governingBody P46 FINISHED
Object Gangseo-gu Office
Gangseo-gu Office is the local administrative authority responsible for providing public services and managing municipal affairs in Seoul’s Gangseo District.
 E186144 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: Gangseo-gu Office | Statement: [Gangseo District, governingBody, Gangseo-gu Office]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gangseo-gu Office
Context triple: [Gangseo District, governingBody, Gangseo-gu Office]
  • A. Sasang-gu Office
    Sasang-gu Office is the local government administrative headquarters responsible for managing public services and municipal affairs in Sasang District, Busan, South Korea.
  • B. Dong-gu
    Dong-gu is an administrative district of the metropolitan city of Ulsan in South Korea, known for its coastal location and industrial facilities.
  • C. Dong-gu
    Dong-gu is a district-level administrative area within the metropolitan city of Daejeon in South Korea.
  • D. Gwaebeop-dong
    Gwaebeop-dong is a neighborhood in Busan, South Korea, known as an administrative subdivision of the city's Sasang District.
  • 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. 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: Gangseo-gu Office
Triple: [Gangseo District, governingBody, Gangseo-gu Office]
Generated description
Gangseo-gu Office is the local administrative authority responsible for providing public services and managing municipal affairs in Seoul’s Gangseo District.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gangseo-gu Office
Target entity description: Gangseo-gu Office is the local administrative authority responsible for providing public services and managing municipal affairs in Seoul’s Gangseo District.
  • A. Sasang-gu Office
    Sasang-gu Office is the local government administrative headquarters responsible for managing public services and municipal affairs in Sasang District, Busan, South Korea.
  • B. Dong-gu
    Dong-gu is a district-level administrative area within the metropolitan city of Daejeon in South Korea.
  • C. Dong-gu
    Dong-gu is an administrative district of the metropolitan city of Ulsan in South Korea, known for its coastal location and industrial facilities.
  • D. Gwaebeop-dong
    Gwaebeop-dong is a neighborhood in Busan, South Korea, known as an administrative subdivision of the city's Sasang District.
  • 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. 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_69a88604618c81908b41f6429c431eb6 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa622e9b08819094960b2329c6e7e6 completed March 6, 2026, 5:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad60a26350819087e7a87b52561143 completed March 8, 2026, 11:42 a.m.
NEDg Description generation batch_69ad61d1806081909268a9a100b326a1 completed March 8, 2026, 11:47 a.m.
NED2 Entity disambiguation (via description) batch_69ad622acf5881908add72069bd2f060 completed March 8, 2026, 11:48 a.m.
Created at: March 4, 2026, 7:28 p.m.