Triple
T11202006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western Chalukya period |
E265062
|
entity |
| Predicate | literaryActivity |
P97836
|
FINISHED |
| Object | growth of Kannada prose |
—
|
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: growth of Kannada prose | Statement: [Western Chalukya period, literaryActivity, growth of Kannada prose]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literaryActivity Context triple: [Western Chalukya period, literaryActivity, growth of Kannada prose]
-
A.
literaryThemeInvolvement
Indicates the involvement or presence of a particular literary theme within a work, passage, or character arc.
-
B.
literaryInterest
Indicates that one entity has an interest in, appreciation of, or engagement with the literary works or writings of another entity.
-
C.
literarySubject
Indicates that one entity serves as the subject, topic, or focus of a literary work created by another entity.
-
D.
literaryScript
Indicates a relationship where an entity serves as the written text or script of a literary work, such as a play, film, or other narrative production.
-
E.
literaryMuseOf
Indicates a relationship in which one entity serves as the creative inspiration or muse for another entity’s literary work.
- 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_69d6aa9eb9248190b20211772621b4bc |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8c36c188190bfa4d5f8e6cbbbea |
completed | April 9, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69d75cf83464819087529d47d025d313 |
completed | April 9, 2026, 8:02 a.m. |
| PDg | Predicate description generation | batch_69d77062271c8190b63da714ab5beff9 |
completed | April 9, 2026, 9:24 a.m. |
Created at: April 8, 2026, 9:29 p.m.