Triple
T7730445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Film Award for Best Children's Film |
E175234
|
entity |
| Predicate | hasLanguageScope |
P397
|
FINISHED |
| Object | all Indian languages |
—
|
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: all Indian languages | Statement: [National Film Award for Best Children's Film, hasLanguageScope, all Indian languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageScope Context triple: [National Film Award for Best Children's Film, hasLanguageScope, all Indian languages]
-
A.
hasLanguageCodeScope
Indicates that a language code is valid or applicable only within a specified scope, context, or domain.
-
B.
hasLanguageContext
Indicates that an entity is associated with or interpreted within a specific language or linguistic context.
-
C.
hasScope
chosen
Indicates that one entity defines, limits, or encompasses the range, extent, or applicability within which another entity operates or is valid.
-
D.
linguisticScope
Indicates the range or domain within language (such as a phrase, clause, or discourse segment) over which a particular linguistic element, feature, or operation has effect.
-
E.
hasLanguagePolicyContext
Indicates that there is an associated language-related policy, rule, or regulatory context governing how language is used or managed in relation to the subject.
- 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_69c6995e912c81909a49a2657103f786 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7074eca4c8190bd51fd1b450729e8 |
completed | March 27, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69c7016a6cf88190b53bf4b958f0f302 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:06 p.m.