Triple

T11355803
Position Surface form Disambiguated ID Type / Status
Subject Sam Yan area, Pathum Wan, Bangkok E268946 entity
Predicate locatedIn P40 FINISHED
Object Bangkok E10237 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: Bangkok | Statement: [Sam Yan area, Pathum Wan, Bangkok, locatedIn, Bangkok]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bangkok
Context triple: [Sam Yan area, Pathum Wan, Bangkok, locatedIn, Bangkok]
  • A. Bangkok chosen
    Bangkok is the vibrant capital and largest city of Thailand, known for its bustling street life, ornate temples, and role as a major economic and cultural hub in Southeast Asia.
  • B. Pattaya
    Pattaya is a major Thai coastal city known for its vibrant nightlife, beaches, and role as a leading international tourist resort.
  • C. Hat Yai
    Hat Yai is a major commercial and transportation hub city in southern Thailand, known for its bustling markets and proximity to the Malaysian border.
  • D. Chiang Mai
    Chiang Mai is a historic city in northern Thailand known for its ancient temples, vibrant night markets, and surrounding mountainous landscapes.
  • E. Seoul–Bangkok
    Seoul–Bangkok is a major international air route connecting the capital cities of South Korea and Thailand, popular for both tourism and business travel.
  • 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_69d6aacbe18081909e5fadb50082dd96 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea404e0c8190befe349b45918b38 completed April 9, 2026, 6:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69e542f294988190bb456326e4184dcb completed April 19, 2026, 9:02 p.m.
Created at: April 8, 2026, 9:33 p.m.