Triple
T13305111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kayin State |
E316915
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Thandaunggyi
Thandaunggyi is a town in southeastern Myanmar known for its cool climate, hilly terrain, and tea and coffee plantations.
|
E1035039
|
NE FINISHED |
How this triple was built (4 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: Thandaunggyi | Statement: [Kayin State, containsTown, Thandaunggyi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thandaunggyi Context triple: [Kayin State, containsTown, Thandaunggyi]
-
A.
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.
-
B.
Myaungmya
Myaungmya is a town in southwestern Myanmar known as an agricultural and riverine trade center within the Ayeyarwady Delta.
-
C.
Myingyan
Myingyan is a town in central Myanmar known as a commercial and transport hub along the Irrawaddy River in the Mandalay Region.
-
D.
Mawlamyine
Mawlamyine is a coastal city in southeastern Myanmar and the capital of Mon State, known historically as an important port and cultural center.
-
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. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Thandaunggyi Triple: [Kayin State, containsTown, Thandaunggyi]
Generated description
Thandaunggyi is a town in southeastern Myanmar known for its cool climate, hilly terrain, and tea and coffee plantations.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Thandaunggyi Target entity description: Thandaunggyi is a town in southeastern Myanmar known for its cool climate, hilly terrain, and tea and coffee plantations.
-
A.
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.
-
B.
Myaungmya
Myaungmya is a town in southwestern Myanmar known as an agricultural and riverine trade center within the Ayeyarwady Delta.
-
C.
Myingyan
Myingyan is a town in central Myanmar known as a commercial and transport hub along the Irrawaddy River in the Mandalay Region.
-
D.
Mawlamyine
Mawlamyine is a coastal city in southeastern Myanmar and the capital of Mon State, known historically as an important port and cultural center.
-
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. chosen
Provenance (5 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_69d806b40ab4819094adf6c374f4811a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d990a76adc8190ab9abcdb79a21ca8 |
completed | April 11, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f262fd88190ba8871f8761a660b |
completed | May 3, 2026, 10:10 a.m. |
| NEDg | Description generation | batch_69f720bb48f081908d67d330dcfc2953 |
completed | May 3, 2026, 10:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f721baaf34819081113c586fae013f |
completed | May 3, 2026, 10:21 a.m. |
Created at: April 9, 2026, 9:28 p.m.