Triple

T17075054
Position Surface form Disambiguated ID Type / Status
Subject Diocesan Boys’ School E414326 entity
Predicate locatedIn P40 FINISHED
Object Mong Kok 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: Mong Kok | Statement: [Diocesan Boys’ School, locatedIn, Mong Kok]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mong Kok
Context triple: [Diocesan Boys’ School, locatedIn, Mong Kok]
  • A. Mong Kok chosen
    Mong Kok is a densely populated, vibrant commercial and residential area in Kowloon, Hong Kong, known for its bustling street markets, neon-lit shopping streets, and lively urban atmosphere.
  • B. Chai Wan
    Chai Wan is a residential and industrial district located at the eastern end of Hong Kong Island.
  • C. Sheung Wan
    Sheung Wan is a historic district on Hong Kong Island known for its blend of traditional Chinese shops, temples, and modern cafes and galleries.
  • D. Kowloon Tong
    Kowloon Tong is an upscale residential and educational neighborhood in Hong Kong known for its low-rise housing, international schools, and proximity to major transport links.
  • E. Sai Ying Pun
    Sai Ying Pun is a historic, densely populated neighborhood on Hong Kong Island known for its mix of traditional shops, trendy cafes, and colonial-era architecture.
  • 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_69d886cef44c8190ba56c44b4e863e64 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dbc47808819088a4ca039689b213 completed April 18, 2026, 7:30 p.m.
Created at: April 10, 2026, 5:34 a.m.