Triple

T637442
Position Surface form Disambiguated ID Type / Status
Subject Thai language E16655 entity
Predicate majorityLanguageIn P11430 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: [Thai language, majorityLanguageIn, Bangkok]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bangkok
Context triple: [Thai language, majorityLanguageIn, 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. Chiang Mai
    Chiang Mai is a historic city in northern Thailand known for its ancient temples, vibrant night markets, and surrounding mountainous landscapes.
  • D. Vientiane
    Vientiane is the capital and largest city of Laos, situated along the Mekong River near the border with Thailand.
  • E. Krabi
    Krabi is a coastal province in southern Thailand renowned for its dramatic limestone cliffs, clear turquoise waters, and island-hopping beaches like Railay and the Phi Phi Islands.
  • 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_69a4936be1c88190af56540324b57da7 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49ee7fdbc8190858e42bb1bfdb3ff completed March 1, 2026, 8:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69a57405d6f48190b55542d50d3a1f22 completed March 2, 2026, 11:27 a.m.
Created at: March 1, 2026, 7:35 p.m.