Triple
T13706369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hakha Chin |
E328651
|
entity |
| Predicate | spokenIn |
P2266
|
FINISHED |
| Object | Myanmar |
E11632
|
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: Myanmar | Statement: [Hakha Chin, spokenIn, Myanmar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Myanmar Context triple: [Hakha Chin, spokenIn, Myanmar]
-
A.
Myanmar
chosen
Myanmar is a Southeast Asian nation bordered by India, China, and Thailand, known for its diverse ethnic groups, Buddhist heritage, and long history of military rule and political turmoil.
-
B.
Burma (until 1937)
Burma (until 1937) was a province administered as part of British India under British colonial rule before becoming a separately governed colony.
-
C.
Thayarwady
Thayarwady is a town in central Myanmar known as an administrative and commercial center within the Bago Region.
-
D.
India and Myanmar
India and Myanmar are neighboring South and Southeast Asian countries that share a long, culturally diverse land border shaped by mountainous terrain and historical trade routes.
-
E.
Thailand
Thailand is a Southeast Asian nation known for its rich Buddhist culture, constitutional monarchy, and role as a regional hub for tourism and trade.
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dcad17732c8190bbd0d73107711c99 |
completed | April 13, 2026, 8:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7943610488190838719ad31207c52 |
completed | May 3, 2026, 6:30 p.m. |
Created at: April 9, 2026, 9:54 p.m.