Triple
T30263886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | বনলতা সেন |
E769578
|
entity |
| Predicate | সাহিত্য_সমালোচনা |
P83910
|
FINISHED |
| Object | প্রায়ই প্রতীকবাদী দৃষ্টিকোণ থেকে বিশ্লেষিত |
—
|
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: প্রায়ই প্রতীকবাদী দৃষ্টিকোণ থেকে বিশ্লেষিত | Statement: [বনলতা সেন, সাহিত্য_সমালোচনা, প্রায়ই প্রতীকবাদী দৃষ্টিকোণ থেকে বিশ্লেষিত]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: সাহিত্য_সমালোচনা Context triple: [বনলতা সেন, সাহিত্য_সমালোচনা, প্রায়ই প্রতীকবাদী দৃষ্টিকোণ থেকে বিশ্লেষিত]
-
A.
literaryCritic
Indicates a relationship where one entity evaluates, analyzes, or interprets the literary works or writings of another entity.
-
B.
literarySubject
Indicates that one entity serves as the subject, topic, or focus of a literary work created by another entity.
-
C.
inLiterature
Indicates that a work, concept, or entity is mentioned, discussed, or represented within a piece of literature.
-
D.
literaryCriticismType
chosen
Indicates the specific kind or category of literary criticism applied to a work, author, or text.
-
E.
literaryLanguage
Indicates that an entity is expressed, written, or communicated using a particular literary or standardized written language.
- 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_69f22484a5f48190b678cd607700bc82 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68a16debc8190a12f5f65ced055d7 |
completed | May 2, 2026, 11:34 p.m. |
| PD | Predicate disambiguation | batch_69f6860def1c81909d79e1f088c4b5e5 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 29, 2026, 7:42 p.m.