Triple
T33637154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Academy Award for Best Foreign Language Film (India's official entry) |
E861728
|
entity |
| Predicate | numberOfSubmissionsPerYear |
P197177
|
FINISHED |
| Object | one 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: one film | Statement: [Academy Award for Best Foreign Language Film (India's official entry), numberOfSubmissionsPerYear, one film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSubmissionsPerYear Context triple: [Academy Award for Best Foreign Language Film (India's official entry), numberOfSubmissionsPerYear, one film]
-
A.
numberOfSubmissions
Indicates the total count of submissions associated with a given entity or context.
-
B.
hasNumberOfOccurrencesPerYear
chosen
Indicates the relationship that specifies how many times something happens within a one-year period.
-
C.
numberOfReleasesPerYear
Indicates the quantity of releases that occur within a single year.
-
D.
finalReportSubmissionYear
Indicates the calendar year in which the final report is formally submitted.
-
E.
acceptsSubmissionsFrom
Indicates that one entity receives and is willing to consider submissions (such as content, proposals, or applications) originating from another 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_69f3498280c48190bcc3494017d14234 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a033d975d788190aafc4be10d6c5c1c |
completed | May 12, 2026, 2:47 p.m. |
| PD | Predicate disambiguation | batch_6a033cc2668481908cb696e57632a68f |
completed | May 12, 2026, 2:44 p.m. |
Created at: May 1, 2026, 1:42 a.m.