Triple
T12928098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daytime Emmy Award for Outstanding Main Title and Graphic Design |
E309298
|
entity |
| Predicate | languageOfEligiblePrograms |
P73062
|
FINISHED |
| Object | primarily English |
—
|
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: primarily English | Statement: [Daytime Emmy Award for Outstanding Main Title and Graphic Design, languageOfEligiblePrograms, primarily English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfEligiblePrograms Context triple: [Daytime Emmy Award for Outstanding Main Title and Graphic Design, languageOfEligiblePrograms, primarily English]
-
A.
notableLanguageOfEligiblePrograms
Indicates that the specified language is a significant or primary language used in the programs that qualify under certain eligibility criteria.
-
B.
offersProgramsInLanguage
Indicates that an entity provides or conducts its programs using a specified language.
-
C.
eligibleLanguage
chosen
Indicates that a particular language satisfies the required conditions to be considered valid or allowed in a given context.
-
D.
languageOfInterpretation
Indicates the language in which something (such as text, speech, or content) is interpreted or understood.
-
E.
languageOfTeachings
Indicates the language in which teachings, lessons, or instructional content are delivered or expressed.
- 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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971ec72a48190aceef10630603d2c |
completed | April 10, 2026, 9:55 p.m. |
| PD | Predicate disambiguation | batch_69d96fab4d0881909a7a4d66bab9aa85 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:42 p.m.