Triple
T25331782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mahishya |
E635168
|
entity |
| Predicate | hasSocialReformOrientation |
P138840
|
FINISHED |
| Object | support for education |
—
|
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: support for education | Statement: [Mahishya, hasSocialReformOrientation, support for education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSocialReformOrientation Context triple: [Mahishya, hasSocialReformOrientation, support for education]
-
A.
isReformOriented
chosen
Indicates that an entity is oriented toward initiating, supporting, or implementing reforms or improvements within a system, policy, or practice.
-
B.
advocatedReformOf
Indicates that one entity publicly supported or promoted changes to another entity, typically aiming to improve or modify its structure, policies, or practices.
-
C.
attitudeTowardReform
Indicates an entity’s stance, opinion, or disposition regarding a proposed or ongoing reform.
-
D.
goalOfReforms
Indicates that a reform or set of reforms is undertaken with the aim or intended objective of achieving a particular outcome.
-
E.
typeOfReforms
Indicates the specific kinds or categories of reforms associated with an entity or situation.
- 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_69e75a9908108190a95427a97020632a |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f60c3b09488190ade1b69ff7f0df0e |
completed | May 2, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69f60b8461ac81908c5bd3d73eed59f4 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 21, 2026, 1:30 p.m.