Triple

T13305082
Position Surface form Disambiguated ID Type / Status
Subject Kayin State E316915 entity
Predicate borderWith P224 FINISHED
Object Tak province E669221 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: Tak province | Statement: [Kayin State, borderWith, Tak province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tak province
Context triple: [Kayin State, borderWith, Tak province]
  • A. Tak province chosen
    Tak province is a mountainous and forested region in western Thailand, known for its border with Myanmar, scenic national parks, and the gateway town of Mae Sot.
  • B. Pernik Province
    Pernik Province is a region in western Bulgaria known for its industrial heritage and proximity to the capital, Sofia.
  • C. Hither Province
    Hither Province was a historical administrative region associated with the ancient Greek city-state of Pylos.
  • D. Sulu Province
    Sulu Province is an island province in the southwestern Philippines, known for its predominantly Muslim population, rich maritime culture, and role as a historical center of the Sultanate of Sulu.
  • E. Chota Province
    Chota Province is an administrative division in northern Peru known for its Andean highland landscapes, agriculture, and traditional cultural festivities.
  • 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_69d806b40ab4819094adf6c374f4811a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990a76adc8190ab9abcdb79a21ca8 completed April 11, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716e3617081909eea9989cf5e7b30 completed May 3, 2026, 9:35 a.m.
Created at: April 9, 2026, 9:28 p.m.