Triple

T7844739
Position Surface form Disambiguated ID Type / Status
Subject National Film Award for Best Film on National Integration E181894 entity
Predicate languageEligibility P73062 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 Film on National Integration, languageEligibility, All Indian languages]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: languageEligibility
Context triple: [National Film Award for Best Film on National Integration, languageEligibility, All Indian languages]
  • A. eligibleLanguage chosen
    Indicates that a particular language satisfies the required conditions to be considered valid or allowed in a given context.
  • B. hasLanguageStatus
    Indicates that an entity has a particular status or condition regarding its language use, recognition, or classification.
  • C. languagesSpoken
    Indicates that an entity is able to communicate using one or more specified languages.
  • D. languageCriterion
    Indicates that a relationship or selection is based on whether something meets a specified language-related requirement or condition.
  • E. languageProvision
    Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by 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_69ca8285d6488190a95d4c02d7354b53 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb163d92fc8190a4efcb08d6b3d404 completed March 31, 2026, 12:33 a.m.
PD Predicate disambiguation batch_69cae91e98988190abd4ece75932c589 completed March 30, 2026, 9:20 p.m.
Created at: March 30, 2026, 4:48 p.m.