Triple
T30263874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | বনলতা সেন |
E769578
|
entity |
| Predicate | সাহিত্যিক_গুরুত্ব |
P15594
|
FINISHED |
| Object | বাংলা সাহিত্যের অন্যতম বিখ্যাত কবিতা |
—
|
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: বাংলা সাহিত্যের অন্যতম বিখ্যাত কবিতা | Statement: [বনলতা সেন, সাহিত্যিক_গুরুত্ব, বাংলা সাহিত্যের অন্যতম বিখ্যাত কবিতা]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: সাহিত্যিক_গুরুত্ব Context triple: [বনলতা সেন, সাহিত্যিক_গুরুত্ব, বাংলা সাহিত্যের অন্যতম বিখ্যাত কবিতা]
-
A.
hasLiterarySignificance
chosen
Indicates that something holds notable importance, influence, or value within the realm of literature or literary studies.
-
B.
literarySubject
Indicates that one entity serves as the subject, topic, or focus of a literary work created by another entity.
-
C.
literaryInfluence
Indicates that one entity has had a significant impact on the style, themes, or development of another entity’s literary work.
-
D.
literaryCritic
Indicates a relationship where one entity evaluates, analyzes, or interprets the literary works or writings of another entity.
-
E.
literaryAuthor
Indicates that one entity is the author or writer of a literary work represented by the other 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_69f22484a5f48190b678cd607700bc82 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f680ab3ba481908d75676fef98820f |
completed | May 2, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69f678ce54b081908c26edfd49e39c60 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 29, 2026, 7:42 p.m.