Triple
T29415785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Film Award for Best Background Score |
E746022
|
entity |
| Predicate | awardNameInHindi |
P180877
|
FINISHED |
| Object | राष्ट्रीय फिल्म पुरस्कार सर्वश्रेष्ठ पृष्ठभूमि संगीत |
—
|
NE NERFINISHED |
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: राष्ट्रीय फिल्म पुरस्कार सर्वश्रेष्ठ पृष्ठभूमि संगीत | Statement: [National Film Award for Best Background Score, awardNameInHindi, राष्ट्रीय फिल्म पुरस्कार सर्वश्रेष्ठ पृष्ठभूमि संगीत]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: awardNameInHindi Context triple: [National Film Award for Best Background Score, awardNameInHindi, राष्ट्रीय फिल्म पुरस्कार सर्वश्रेष्ठ पृष्ठभूमि संगीत]
-
A.
awardNameInBengali
Indicates the name of an award as expressed or written in the Bengali language.
-
B.
hasIndianLaureate
Indicates that an entity has at least one laureate who is of Indian nationality or origin.
-
C.
awardName
Indicates the specific name or title of an award associated with an entity.
-
D.
numberOfNationalFilmAwards
Indicates the total count of national film awards that have been received by the referenced entity.
-
E.
nationalFilmAwardsWon
Indicates that an entity has received one or more National Film Awards, specifying a winning achievement in that award system.
- 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_69f0a79f6d5c8190a350baed0157e06f |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f757898fe48190b124dc7301672623 |
completed | May 3, 2026, 2:11 p.m. |
| PD | Predicate disambiguation | batch_69f754c484348190948d2a04ff228fb1 |
completed | May 3, 2026, 1:59 p.m. |
| PDg | Predicate description generation | batch_69f75788d40c819083bf2567b3091585 |
completed | May 3, 2026, 2:11 p.m. |
Created at: April 28, 2026, 3:01 p.m.