Triple
T12748960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western Myanmar |
E304680
|
entity |
| Predicate | hasPortCity |
P2745
|
FINISHED |
| Object | Kyaukphyu |
E309793
|
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: Kyaukphyu | Statement: [Western Myanmar, hasPortCity, Kyaukphyu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kyaukphyu Context triple: [Western Myanmar, hasPortCity, Kyaukphyu]
-
A.
Kyaukphyu
chosen
Kyaukphyu is a coastal town in western Myanmar that serves as a strategic deep-water port and hub for regional trade and energy projects.
-
B.
Nyaung-U
Nyaung-U is a historic town in central Myanmar best known as the main gateway to the ancient temple plain of Bagan.
-
C.
Mangaldoi
Mangaldoi is a town in the Indian state of Assam that serves as an important administrative and commercial center for the surrounding region.
-
D.
Moulamein
Moulamein is a small rural town in the Riverina region of New South Wales, Australia, known for its historic buildings and riverside setting.
-
E.
Kawthaung
Kawthaung is a coastal town in southern Myanmar that serves as a key gateway for cross-border trade and travel with Thailand.
- 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96bd75f508190aaae0969f33d1523 |
completed | April 10, 2026, 9:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f67c964c508190b4d6a094b388280b |
completed | May 2, 2026, 10:37 p.m. |
Created at: April 9, 2026, 5:27 p.m.