Triple

T22402913
Position Surface form Disambiguated ID Type / Status
Subject Zhanqiao Pier E553804 entity
Predicate locatedIn P40 FINISHED
Object Shinan District 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: Shinan District | Statement: [Zhanqiao Pier, locatedIn, Shinan District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shinan District
Context triple: [Zhanqiao Pier, locatedIn, Shinan District]
  • A. Shinan District chosen
    Shinan District is a central coastal district of Qingdao, China, known for its historic European-style architecture, scenic seaside areas, and role as the city’s political and cultural hub.
  • B. Kaifu District
    Kaifu District is an urban administrative district of Changsha, the capital city of Hunan Province in south-central China.
  • C. Hana District
    Hana District is a rural administrative region on the eastern side of Maui, Hawaii, known for its remote coastal landscapes, lush rainforests, and the scenic Road to Hana.
  • D. 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.
  • E. Shinanomachi district
    Shinanomachi district is a neighborhood in Shinjuku, Tokyo, known for its central location, proximity to major rail lines, and mix of residential, medical, and institutional facilities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e4da7048190b4387d422a9a0de5 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f158b565c48190b0f6c19f17995b40 completed April 29, 2026, 1:02 a.m.
Created at: April 16, 2026, 8:46 p.m.