Triple
T13047336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khorat Plateau |
E327357
|
entity |
| Predicate | drainedBy |
P165
|
FINISHED |
| Object | Mun River |
E175295
|
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: Mun River | Statement: [Khorat Plateau, drainedBy, Mun River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mun River Context triple: [Khorat Plateau, drainedBy, Mun River]
-
A.
Mun River
chosen
The Mun River is a significant river in northeastern Thailand that drains much of the Isan region before joining the Mekong.
-
B.
Mamu River
The Mamu River is a lesser-known river in western Brazil that serves as a tributary within the extensive Amazon Basin water system.
-
C.
Ampoi River
The Ampoi River is a tributary watercourse in Romania that flows through Alba County before joining the Mureș River.
-
D.
Tuy River
The Tuy River is a significant river in northern Venezuela that flows through the Miranda state and supports nearby cities such as Ocumare del Tuy.
-
E.
Nanoi River
Nanoi River is a regional river flowing through Assam’s Darrang district in northeastern India.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d9805125e481908ed56f708de98a9e |
completed | April 10, 2026, 10:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f73053a1888190a234e8c119a4202a |
completed | May 3, 2026, 11:24 a.m. |
Created at: April 9, 2026, 8:57 p.m.