Triple
T25296894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Filmfare Award for Best Director – Telugu |
E634238
|
entity |
| Predicate | hasAwardedWorkLanguage |
P158363
|
FINISHED |
| Object | Telugu |
—
|
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: Telugu | Statement: [Filmfare Award for Best Director – Telugu, hasAwardedWorkLanguage, Telugu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAwardedWorkLanguage Context triple: [Filmfare Award for Best Director – Telugu, hasAwardedWorkLanguage, Telugu]
-
A.
hasWorkedInLanguage
Indicates that an entity has performed work or professional activities using a particular language.
-
B.
usesWorkingLanguagesOf
Indicates that one entity employs or operates using the working languages associated with another entity.
-
C.
hasOfficialLanguageOfWork
Indicates that an entity uses a specified language as its official medium for conducting work or formal activities.
-
D.
hasWorkTranslatedInto
Indicates that a work has been translated into a specified language or target work.
-
E.
hasAwardedWorkType
Indicates that an entity has granted or is associated with a specific type or category of work that has received an award.
- 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_69e75a9503d48190b80a005c6af0cb50 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f48fd2e5ec8190965046138f838057 |
completed | May 1, 2026, 11:34 a.m. |
| PD | Predicate disambiguation | batch_69f45d06d0388190b36ecde92013624a |
completed | May 1, 2026, 7:57 a.m. |
| PDg | Predicate description generation | batch_69f465699c9c8190ac7b4b32b782550c |
completed | May 1, 2026, 8:33 a.m. |
Created at: April 21, 2026, 1:22 p.m.