Triple
T8558814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tamil Nadu State Film Awards |
E202639
|
entity |
| Predicate | notableLanguageRequirement |
P73189
|
FINISHED |
| Object | films in Tamil language |
—
|
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: films in Tamil language | Statement: [Tamil Nadu State Film Awards, notableLanguageRequirement, films in Tamil language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableLanguageRequirement Context triple: [Tamil Nadu State Film Awards, notableLanguageRequirement, films in Tamil language]
-
A.
eligibleLanguage
Indicates that a particular language satisfies the required conditions to be considered valid or allowed in a given context.
-
B.
notableLanguageOfEligiblePrograms
Indicates that the specified language is a significant or primary language used in the programs that qualify under certain eligibility criteria.
-
C.
notableRecruitingSkill
Indicates that an entity is recognized for having significant or distinguished ability in recruiting others.
-
D.
recruitmentRequirement
Indicates that a certain condition, qualification, or criterion must be satisfied for an entity to be eligible for recruitment or hiring.
-
E.
notableLanguageOfEligibleFilms
chosen
Indicates that there is a notable language associated with the set of films that qualify as eligible under a given criterion or program.
- 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_69ca8326e6c881908ff720d6abaebdc5 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe9485dd88190bc2cf2adf39d48ee |
completed | March 31, 2026, 3:33 p.m. |
| PD | Predicate disambiguation | batch_69cbd1160fcc8190aa380a73610af731 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:20 p.m.