Triple
T31399535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prasun |
E800956
|
entity |
| Predicate | isRegionallyUsedIn |
P15483
|
FINISHED |
| Object | South Asia |
—
|
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: South Asia | Statement: [Prasun, isRegionallyUsedIn, South Asia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isRegionallyUsedIn Context triple: [Prasun, isRegionallyUsedIn, South Asia]
-
A.
usedInRegion
Indicates that something is utilized or applied within a specific geographic or administrative region.
-
B.
usedInCountryOrRegion
Indicates that something (such as an item, concept, or practice) is utilized or applied within a specified country or region.
-
C.
hasTypicalUsageRegion
chosen
Indicates that something is most commonly or characteristically used within a particular geographic region.
-
D.
isRegional
Indicates that something pertains to, is characteristic of, or is limited to a specific geographic region or area.
-
E.
usedInAllRegionsOf
Indicates that something is utilized or applied in every region within a specified scope or system.
- F. None of above.
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_69f224ea9998819086ae2e4f4f4091c8 |
completed | April 29, 2026, 3:34 p.m. |
| NER | Named-entity recognition | batch_69f6a916d2e08190bafc01cba73b6469 |
completed | May 3, 2026, 1:47 a.m. |
| PD | Predicate disambiguation | batch_69f6a7548eb48190a69b60a3c6ad53b9 |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 29, 2026, 9:19 p.m.