Triple
T29271470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BFJA Award |
E742127
|
entity |
| Predicate | notableLanguageCategory |
P125434
|
FINISHED |
| Object | Best Bengali Film |
—
|
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: Best Bengali Film | Statement: [BFJA Award, notableLanguageCategory, Best Bengali Film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableLanguageCategory Context triple: [BFJA Award, notableLanguageCategory, Best Bengali Film]
-
A.
notableLanguageGroup
Indicates that there is a significant or noteworthy association between an entity and a particular language group.
-
B.
notableLanguageOfActivity
Indicates that a language is prominently used or recognized in connection with a particular activity or domain of activity.
-
C.
notableLanguageOfWorks
chosen
Indicates that a particular language is especially prominent or significant among the works created by an entity.
-
D.
languageCategory
Indicates the classification relationship where a language is assigned to a particular linguistic or functional category.
-
E.
notableProgrammingCategory
Indicates that an entity is recognized as belonging to a significant or distinguished category within the domain of programming.
- 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_69f0912124d48190a046642b69407f4c |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_6a033029023481909d9fa4a76b954879 |
completed | May 12, 2026, 1:50 p.m. |
| PD | Predicate disambiguation | batch_6a032d9f1fa48190bd1c94a8f930d02c |
completed | May 12, 2026, 1:39 p.m. |
Created at: April 28, 2026, 12:48 p.m.