Triple
T10444074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aavarana |
E246238
|
entity |
| Predicate | influencedPublicDiscourseOn |
P9239
|
FINISHED |
| Object | history textbooks in 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: history textbooks in India | Statement: [Aavarana, influencedPublicDiscourseOn, history textbooks in India]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influencedPublicDiscourseOn Context triple: [Aavarana, influencedPublicDiscourseOn, history textbooks in India]
-
A.
influencedDiscussionOf
chosen
Indicates that one entity had an effect on the way another entity was discussed, framed, or debated.
-
B.
politicalInfluenceIn
Indicates that an entity exerts or holds political influence within a specified place, jurisdiction, or political context.
-
C.
hasSignificantInfluenceIn
Indicates that one entity exerts a substantial impact or shaping effect on another entity within a particular domain, context, or outcome.
-
D.
ideologicalInfluence
Indicates that one entity’s beliefs, values, or doctrines shape, guide, or significantly affect the ideology of another entity.
-
E.
influentialFrom
Indicates that one entity has exerted influence on another, contributing to or shaping the latter’s ideas, behavior, or development.
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fe083cd881909d2d8ad75d1d94cb |
completed | April 7, 2026, 12:52 p.m. |
| PD | Predicate disambiguation | batch_69d4fb73a5e48190a8df4775bc5da80f |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:16 p.m.