Triple
T9125640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yangon Central Railway Station |
E218960
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Mawlamyine |
E402287
|
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: Mawlamyine | Statement: [Yangon Central Railway Station, connectsTo, Mawlamyine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mawlamyine Context triple: [Yangon Central Railway Station, connectsTo, Mawlamyine]
-
A.
Mawlamyine
chosen
Mawlamyine is a coastal city in southeastern Myanmar and the capital of Mon State, known historically as an important port and cultural center.
-
B.
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.
-
C.
Kawthaung
Kawthaung is a coastal town in southern Myanmar that serves as a key gateway for cross-border trade and travel with Thailand.
-
D.
Myitkyina
Myitkyina is the capital of Kachin State in northern Myanmar, known as a key regional center and transport hub near the upper reaches of the Irrawaddy River.
-
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_69ca83dddd548190983b96c664f7f367 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8b8970881909c3b2c67fc131627 |
completed | April 1, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d047c55a988190bf2dd63a0d0a2743 |
completed | April 3, 2026, 11:05 p.m. |
Created at: March 30, 2026, 7:17 p.m.