Triple

T7978789
Position Surface form Disambiguated ID Type / Status
Subject Namhang Bridge E185512 entity
Predicate connectsDistrict P2564 FINISHED
Object Seo-gu E173338 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: Seo-gu | Statement: [Namhang Bridge, connectsDistrict, Seo-gu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seo-gu
Context triple: [Namhang Bridge, connectsDistrict, Seo-gu]
  • A. Seo-gu chosen
    Seo-gu is a district of the metropolitan city of Daejeon in South Korea, known for its residential areas, commercial centers, and educational institutions.
  • B. Seo-gu
    Seo-gu is an administrative district in the city of Daegu, South Korea, known primarily as a residential and commercial urban area.
  • C. Sasang-gu
    Sasang-gu is an administrative district in Busan, South Korea, known for its transportation hubs, industrial areas, and mixed residential-commercial neighborhoods.
  • D. Kangseo-gu
    Kangseo-gu is the romanized name of Gangseo District, an administrative district of Seoul, South Korea.
  • E. Sŏch'o-gu
    Sŏch'o-gu is the McCune–Reischauer romanization of Seocho District, a major administrative and residential area in southern Seoul, South Korea.
  • 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_69ca829851908190b4e03829353ee7c3 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3bf84b1081908e60a556d984aad6 completed March 31, 2026, 3:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69cef298986c8190a253d5c61310a23a completed April 2, 2026, 10:50 p.m.
Created at: March 30, 2026, 5:14 p.m.