Triple

T7206799
Position Surface form Disambiguated ID Type / Status
Subject Incheon Gwangyeoksi E148684 entity
Predicate hasDistrict P459 FINISHED
Object Seo District E159654 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 District | Statement: [Incheon Gwangyeoksi, hasDistrict, Seo District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seo District
Context triple: [Incheon Gwangyeoksi, hasDistrict, Seo District]
  • A. Seo District chosen
    Seo District is a western coastal district of Incheon, South Korea, known for its industrial complexes, port facilities, and growing residential areas.
  • B. Shapingba District
    Shapingba District is a major urban district of Chongqing, China, known for its universities, historical sites, and role as an educational and cultural center of the city.
  • C. Hongo district
    Hongo district is a historic and academic neighborhood in Tokyo’s Bunkyō ward, known for institutions like the University of Tokyo and its traditional residential character.
  • D. Tsuzuki District
    Tsuzuki District is a former administrative district that once existed within Kyoto Prefecture in Japan.
  • E. Shenkeng District
    Shenkeng District is a suburban district of New Taipei City in northern Taiwan, best known for its historic old street and specialty stinky tofu cuisine.
  • 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_69c687e8cf188190b5f3ecffd681f04e completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6e969c5fc819096bc03bfba12d0cf completed March 27, 2026, 8:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7bfc0ac008190b3ea46b4e5f13287 completed March 28, 2026, 11:47 a.m.
Created at: March 27, 2026, 2:52 p.m.