Triple
T15984143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sittaung River basin |
E387647
|
entity |
| Predicate | hasMajorCityInBasin |
P33130
|
FINISHED |
| Object | Taungoo |
E432154
|
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: Taungoo | Statement: [Sittaung River basin, hasMajorCityInBasin, Taungoo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taungoo Context triple: [Sittaung River basin, hasMajorCityInBasin, Taungoo]
-
A.
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.
-
B.
Taunggyi
Taunggyi is a major city in eastern Myanmar known as an administrative, cultural, and commercial center in the Shan region.
-
C.
Kengtung
Kengtung is a historic town in eastern Myanmar’s Shan State, known as a cultural center of the Tai ethnic groups and a gateway to the Golden Triangle region.
-
D.
Toungoo
chosen
Toungoo is a historic city in Myanmar that served as the capital of a powerful Burmese dynasty and a key military and trading center in the region.
-
E.
Moulamein
Moulamein is a small rural town in the Riverina region of New South Wales, Australia, known for its historic buildings and riverside setting.
- 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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e15756d6488190ac35da00e96ce21d |
completed | April 16, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffcf1abad48190a42510605c30d0b3 |
completed | May 10, 2026, 12:19 a.m. |
Created at: April 10, 2026, 4:54 a.m.