Triple

T20049877
Position Surface form Disambiguated ID Type / Status
Subject Shekou Metro Station E499164 entity
Predicate serves P98 FINISHED
Object Shekou area 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 area | Statement: [Shekou Metro Station, serves, Shekou area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shekou area
Context triple: [Shekou Metro Station, serves, Shekou area]
  • A. Shekou Subdistrict chosen
    Shekou Subdistrict is a coastal urban area in Shenzhen’s Nanshan District known for its port, expatriate community, and role as an early hub of China’s economic reform and opening-up.
  • B. Nanshi area
    The Nanshi area is Shanghai’s historic old city quarter, known for its traditional streets, markets, and cultural heritage within the modern Huangpu District.
  • C. Xinqiao area
    Xinqiao area is a district in Hefei, Anhui Province, China, known for hosting the city’s major international airport and related urban development.
  • D. Caishikou area
    The Caishikou area is a historic commercial and residential neighborhood in central Beijing known for its traditional markets, dense urban fabric, and proximity to major city landmarks.
  • E. Shekou port area
    Shekou port area is a major coastal district in Shenzhen known for its busy container port, ferry terminals, and surrounding commercial and residential developments.
  • 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_69da6276bcf48190aabbf279192a5fb4 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6632cccb481908278c8b2930a8c26 completed April 20, 2026, 5:32 p.m.
Created at: April 11, 2026, 3:37 p.m.