Triple
T13047421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mittraphap Road |
E327359
|
entity |
| Predicate | locatedInRegion |
P40
|
FINISHED |
| Object | Isan |
E327356
|
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: Isan | Statement: [Mittraphap Road, locatedInRegion, Isan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Isan Context triple: [Mittraphap Road, locatedInRegion, Isan]
-
A.
Isan
chosen
Isan is a culturally distinct and predominantly rural region in northeastern Thailand known for its Lao-influenced language, cuisine, and traditions.
-
B.
Isan people
The Isan people are a Lao-speaking ethnic group of northeastern Thailand known for their distinct culture, language, and traditions that blend Lao and Thai influences.
-
C.
Trièves region
The Trièves region is a rural area in the French Prealps known for its dramatic mountain scenery, traditional villages, and outdoor recreation opportunities.
-
D.
Gascogne
Gascogne is a historic cultural region in southwestern France known for its Gascon language, rich rural traditions, and distinctive cuisine including Armagnac and foie gras.
-
E.
Dioise
Dioise is the French demonym referring to inhabitants of the town of Die in the Drôme department of southeastern France.
- 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_69f716baf00881909a1a11d36cdb8d42 |
completed | May 3, 2026, 9:34 a.m. |
Created at: April 9, 2026, 8:57 p.m.