Triple

T18396222
Position Surface form Disambiguated ID Type / Status
Subject Shekou E449877 entity
Predicate hasFeature P182 FINISHED
Object Sea World plaza 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: Sea World plaza | Statement: [Shekou, hasFeature, Sea World plaza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sea World plaza
Context triple: [Shekou, hasFeature, Sea World plaza]
  • A. Sea World Plaza chosen
    Sea World Plaza is a popular waterfront commercial and entertainment complex in Shenzhen’s Shekou area, known for its shopping, dining, and lively nightlife centered around a landlocked cruise ship.
  • B. Sea World Drive
    Sea World Drive is a major roadway in San Diego that provides primary access to the SeaWorld theme park and the surrounding Mission Bay area.
  • C. Sea World
    Sea World is a marine-themed amusement park and oceanarium on Australia's Gold Coast, known for its marine animal exhibits, shows, and rides.
  • D. Marine World
    Marine World was a marine-themed animal park and oceanarium that later evolved into the broader amusement and wildlife park now known as Six Flags Discovery Kingdom.
  • E. Sea World Metro Station
    Sea World Metro Station is a Shenzhen Metro station serving the popular Sea World commercial and entertainment area in the Shekou subdistrict of Nanshan District, China.
  • 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_69d8b9fab8a8819086a9ddc0871715e0 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e51846bb4c8190990f42a792a78ee0 completed April 19, 2026, 6 p.m.
Created at: April 10, 2026, 10:46 a.m.