Triple
T7523648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kawthaung |
E177836
|
entity |
| Predicate | separatedFrom |
P243
|
FINISHED |
| Object | Ranong |
E178430
|
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: Ranong | Statement: [Kawthaung, separatedFrom, Ranong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ranong Context triple: [Kawthaung, separatedFrom, Ranong]
-
A.
Ranong province
chosen
Ranong province is a coastal province in southern Thailand known for its mountainous rainforest terrain, high rainfall, and location along the Andaman Sea near the Myanmar border.
-
B.
Tonsawang
Tonsawang is an Austronesian language spoken by the Tonsawang people in North Sulawesi, Indonesia.
-
C.
Thongduang
Thongduang was the birth name of King Rama I of Siam, the founder and first monarch of Thailand’s Chakri Dynasty.
-
D.
Mae Sot
Mae Sot is a Thai border town in Tak Province known as a major hub for cross-border trade and migration with Myanmar and for its numerous refugee and humanitarian aid organizations.
-
E.
Laem Chabang
Laem Chabang is Thailand’s largest deep-sea commercial port and a major hub for maritime trade in Southeast Asia.
- 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_69c69f29bf3081909a146aec7755f185 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f7c4f32081908b5162f4551adb6d |
completed | March 27, 2026, 9:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c856b369c88190b8a9a196e2166f9f |
completed | March 28, 2026, 10:31 p.m. |
Created at: March 27, 2026, 3:46 p.m.