Triple
T25282158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harikatha (Tamil tradition) |
E633849
|
entity |
| Predicate | drawsFromText |
P158333
|
FINISHED |
| Object | other Puranas |
—
|
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: other Puranas | Statement: [Harikatha (Tamil tradition), drawsFromText, other Puranas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drawsFromText Context triple: [Harikatha (Tamil tradition), drawsFromText, other Puranas]
-
A.
drawsFromText
chosen
Indicates that something is created, derived, or generated using information or content taken from a given text.
-
B.
draws
Indicates that one entity creates a visual representation or image of another entity.
-
C.
drawnTo
Indicates that one entity is attracted or pulled toward another entity, whether physically, emotionally, or conceptually.
-
D.
textBy
Indicates that a given text or written content was authored or produced by a particular entity.
-
E.
textCharacter
Indicates that one entity is a character (such as a letter, digit, or symbol) within a piece of text associated with another entity.
- 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_69e75a9402fc81909362ca85277c06d9 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f497bc12b881908fe3386c66252bf6 |
completed | May 1, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69f49377411c8190b2188de444d76795 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 21, 2026, 1:19 p.m.