Triple
T19184745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Satish Ranjan Das |
E469671
|
entity |
| Predicate | advocatedModel |
P33
|
FINISHED |
| Object | public school model for India |
—
|
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: public school model for India | Statement: [Satish Ranjan Das, advocatedModel, public school model for India]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: advocatedModel Context triple: [Satish Ranjan Das, advocatedModel, public school model for India]
-
A.
adoptedModel
Indicates that one entity has formally chosen, accepted, or implemented another entity as its preferred model or standard.
-
B.
advocates
chosen
Indicates that one entity publicly supports, recommends, or argues in favor of another entity or its interests.
-
C.
possibleModel
Indicates that one entity can serve as a potential or candidate model or template for another entity.
-
D.
advocatesIn
Indicates that an entity actively supports, promotes, or argues in favor of something within a particular context, domain, or setting.
-
E.
advocatesAgainst
Indicates that one entity actively opposes, argues against, or campaigns to prevent or stop another entity, action, or idea.
- 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_69d8dd0ad9088190a173b32657ae2e7a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f61f1d9c8190b67555383d821958 |
completed | April 20, 2026, 9:47 a.m. |
| PD | Predicate disambiguation | batch_69e4b9bb158481909478ca2e06f3ba39 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:07 p.m.