Triple
T7872844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hyderabad-Karnataka |
E182779
|
entity |
| Predicate | aimOfSpecialStatus |
P79487
|
FINISHED |
| Object | reducing regional disparities |
—
|
LITERAL 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: reducing regional disparities | Statement: [Hyderabad-Karnataka, aimOfSpecialStatus, reducing regional disparities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aimOfSpecialStatus Context triple: [Hyderabad-Karnataka, aimOfSpecialStatus, reducing regional disparities]
-
A.
conservationStatus
Indicates the level of risk or protection category assigned to an entity, typically reflecting how threatened it is with extinction or decline.
-
B.
biosphereReserveType
Indicates the specific classification or category of a biosphere reserve within a defined typology or management framework.
-
C.
countryProtectedAreaStatus
Indicates the legal or administrative protection status that a country assigns to a specific area or region.
-
D.
typeOfConservation
Indicates the specific kind or category of conservation practice, method, or approach that applies to an entity or situation.
-
E.
wildlifeProtectionStatus
Indicates the level or type of legal or conservation protection currently applied to wildlife.
- F. None of above. chosen
Provenance (4 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_69ca828a17248190b46defe758bc5ad3 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39a6d93881908d68386e49bea1e3 |
completed | March 31, 2026, 3:04 a.m. |
| PD | Predicate disambiguation | batch_69cae928e1b88190b0620f4c4f03bc7d |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf786ec748190b6347b0c94335550 |
completed | March 30, 2026, 10:21 p.m. |
Created at: March 30, 2026, 4:56 p.m.