Triple
T22676681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salavan Province |
E560362
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Salavan |
—
|
NE NERFINISHED |
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: Salavan | Statement: [Salavan Province, hasSettlement, Salavan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Salavan Context triple: [Salavan Province, hasSettlement, Salavan]
-
A.
Salavan
chosen
Salavan is a town in southern Laos that serves as the administrative and economic center of Salavan Province.
-
B.
Muang Khoun
Muang Khoun is a historic town in northern Laos that once served as the royal and administrative center of the Phuan kingdom and remains known for its ancient temples and war-scarred heritage.
-
C.
Sasin
Sasin is a leading graduate business school based in Bangkok, Thailand, known for its MBA and executive education programs.
-
D.
Yasothon
Yasothon is a provincial city in northeastern Thailand known for its annual rocket festival and strong Isan cultural traditions.
-
E.
Sangkhlaburi
Sangkhlaburi is a remote Thai town near the Myanmar border, known for its cultural mix of Thai, Mon, and Karen communities and its iconic wooden Mon Bridge over the Songkalia River.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2454bfd00819099115715a22cb057 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1785ca1e08190af1a6cdb51ca4fce |
completed | April 29, 2026, 3:17 a.m. |
Created at: April 17, 2026, 3:11 p.m.