Triple
T15876361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rakhine State |
E384961
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Buthidaung |
E1004218
|
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: Buthidaung | Statement: [Rakhine State, hasCity, Buthidaung]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Buthidaung Context triple: [Rakhine State, hasCity, Buthidaung]
-
A.
Buthidaung
chosen
Buthidaung is a town in Myanmar’s Rakhine State, known for its ethnically diverse population and proximity to the border with Bangladesh.
-
B.
Mawlamyine
Mawlamyine is a coastal city in southeastern Myanmar and the capital of Mon State, known historically as an important port and cultural center.
-
C.
Nyaungshwe
Nyaungshwe is a popular lakeside town in Myanmar that serves as the main gateway and tourist hub for visiting Inle Lake in Shan State.
-
D.
Myingyan
Myingyan is a town in central Myanmar known as a commercial and transport hub along the Irrawaddy River in the Mandalay Region.
-
E.
Amarapura
Amarapura is a former royal city in Myanmar renowned for its role as an early Burmese capital and for landmarks such as the U Bein Bridge.
- 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_69d86da4e86481909f1325fdc971b5ec |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e155fdc1b881909d1c82c4c66a195a |
completed | April 16, 2026, 9:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa950a890819092bc1e8895034593 |
completed | May 9, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:51 a.m.