Triple

T12898304
Position Surface form Disambiguated ID Type / Status
Subject Dusit District E308549 entity
Predicate nearby P350 FINISHED
Object Bang Sue District E1023161 NE FINISHED

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: Bang Sue District | Statement: [Dusit District, nearby, Bang Sue District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bang Sue District
Context triple: [Dusit District, nearby, Bang Sue District]
  • A. Bang Sue district chosen
    Bang Sue district is a major administrative area in Bangkok, Thailand, known as a key transportation hub featuring large rail and bus terminals.
  • B. Watthana District
    Watthana District is a central Bangkok district known for its bustling commercial areas, nightlife, and upscale residential neighborhoods.
  • C. Sai Mai District
    Sai Mai District is a residential and suburban district in northern Bangkok, Thailand, known for its growing communities and proximity to Don Mueang Airport.
  • D. Bang Phlat District
    Bang Phlat District is a riverside administrative area of Bangkok, Thailand, known for its mix of residential neighborhoods, local commerce, and access to major city landmarks.
  • E. Bang Rak District
    Bang Rak District is a central district of Bangkok, Thailand, known for its commercial areas, embassies, and major transportation hubs.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d7bdf7c1f0819098102569a8d8cbf5 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9717f3fc48190b61c8f6f36cd0725 completed April 10, 2026, 9:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69fba1af38248190a85d0fa3a26c3d08 completed May 6, 2026, 8:16 p.m.
Created at: April 9, 2026, 5:40 p.m.