Triple
T11738994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chitpavan Brahmins |
E279102
|
entity |
| Predicate | socialReformInvolvement |
P11461
|
FINISHED |
| Object | women's 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: women's education | Statement: [Chitpavan Brahmins, socialReformInvolvement, women's education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: socialReformInvolvement Context triple: [Chitpavan Brahmins, socialReformInvolvement, women's education]
-
A.
socialReformFocus
Indicates a focus on changing or improving social structures, policies, or conditions as part of a reform effort.
-
B.
socialContribution
Indicates that an entity engages in actions or provides resources that benefit society or a community beyond its own direct interests.
-
C.
civicActivity
Indicates participation in or performance of activities related to civic engagement, public service, or community involvement.
-
D.
socialGroupInvolved
Indicates that a particular social group participates in, is affected by, or is otherwise involved in the specified event or situation.
-
E.
areaOfActivism
chosen
Indicates the specific social, political, or environmental cause or issue that an entity actively advocates for or works to change.
- 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_69d6aaffec6881908bead509e8621742 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4ef1c4881909ad36dc27b1fe193 |
completed | April 10, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69d88a7f51248190bf492bd7509b5413 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:41 p.m.