Triple

T17946521
Position Surface form Disambiguated ID Type / Status
Subject Sea World Plaza E448716 entity
Predicate locatedIn P40 FINISHED
Object Shekou 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: Shekou | Statement: [Sea World Plaza, locatedIn, Shekou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shekou
Context triple: [Sea World Plaza, locatedIn, Shekou]
  • A. Shekou chosen
    Shekou is a coastal district in Shenzhen, China, known as a major transportation and commercial hub with significant port facilities and expatriate communities.
  • B. Caishikou
    Caishikou is a subway station in central Beijing that serves as an important stop on the city’s urban rail network.
  • C. Jian'ou
    Jian'ou is a county-level city in northern Fujian Province, China, administered by the prefecture-level city of Nanping and known for its historical and cultural heritage.
  • D. Tangkou Town
    Tangkou Town is a gateway settlement at the foot of Huangshan (Yellow Mountain) in Anhui, China, serving as a primary base for tourists visiting the scenic area and its hot springs.
  • E. Kwang-Chou-Wan
    Kwang-Chou-Wan was a small leased territory in southern China that served as a French colonial enclave administered as part of French Indochina in the late 19th and early 20th centuries.
  • 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_69d8b9f8cca8819099836916c56b7c95 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4ad99df408190a8a4e3d21c03fe71 completed April 19, 2026, 10:25 a.m.
Created at: April 10, 2026, 10:21 a.m.