Triple
T5871137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WLS-TV |
E130516
|
entity |
| Predicate | primaryLanguageOfAudience |
P40556
|
FINISHED |
| Object | 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: English | Statement: [WLS-TV, primaryLanguageOfAudience, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryLanguageOfAudience Context triple: [WLS-TV, primaryLanguageOfAudience, English]
-
A.
primaryLanguageOf
Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
-
B.
primaryLanguageMarket
Indicates that a particular language is the main or dominant language used within a given market or market segment.
-
C.
dominantMediaLanguage
chosen
Indicates that one language is the primary or most prevalent medium of communication used in a given media context or outlet.
-
D.
primaryLanguageConcerned
Indicates that the relationship or action specifically involves or pertains to the main or principal language in question.
-
E.
primaryLanguageContact
Indicates that one language serves as the main or dominant medium of communication in a particular contact situation between language communities.
- 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_69c0085047dc8190af24e311edad3c07 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0432fea5881909f5c291dd8db6105 |
completed | March 22, 2026, 7:29 p.m. |
| PD | Predicate disambiguation | batch_69c033499ca08190bd26cee5b03f6306 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:56 p.m.