Triple

T1564985
Position Surface form Disambiguated ID Type / Status
Subject Chiang Mai E33411 entity
Predicate nativeName P15 FINISHED
Object เชียงใหม่ E33411 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: เชียงใหม่ | Statement: [Chiang Mai, nativeName, เชียงใหม่]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: เชียงใหม่
Context triple: [Chiang Mai, nativeName, เชียงใหม่]
  • A. Chiang Mai chosen
    Chiang Mai is a historic city in northern Thailand known for its ancient temples, vibrant night markets, and surrounding mountainous landscapes.
  • B. Mae Hong Son Province
    Mae Hong Son Province is a mountainous, remote region in northern Thailand known for its significant Karen population, misty landscapes, and forested border with Myanmar.
  • C. Mandalay
    Mandalay is a major cultural and economic center in central Myanmar, historically known as the last royal capital of the Burmese kingdom.
  • D. Chiengmai
    Chiengmai is an alternative spelling of Chiang Mai, a major cultural and historical city in northern Thailand known for its temples and mountainous surroundings.
  • E. Lashio
    Lashio is a key town in northern Myanmar that historically served as an important transport and trade hub, particularly during World War II as the inland gateway to the Burma Road.
  • 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_69a885f11b048190935025a035302715 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa621242188190a7e1deeada7688d8 completed March 6, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad51af2de8819087d287d65aabbf1a completed March 8, 2026, 10:38 a.m.
Created at: March 4, 2026, 7:27 p.m.