Triple
T10178932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shamshad TV |
E235930
|
entity |
| Predicate | primaryLanguageOfContent |
P40556
|
FINISHED |
| Object | Pashto |
—
|
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: Pashto | Statement: [Shamshad TV, primaryLanguageOfContent, Pashto]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryLanguageOfContent Context triple: [Shamshad TV, primaryLanguageOfContent, Pashto]
-
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.
contentLanguage
Indicates the language in which the content is expressed or intended to be understood.
-
C.
primaryLanguageSide1
Indicates that the specified language is the main or dominant language associated with the first participant or side in a relationship.
-
D.
primaryLanguageMarket
Indicates that a particular language is the main or dominant language used within a given market or market segment.
-
E.
dominantMediaLanguage
chosen
Indicates that one language is the primary or most prevalent medium of communication used in a given media context or outlet.
- 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_69ca84d1d5f88190ab878a1021ecff68 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdecd620808190892c6e3074500280 |
completed | April 2, 2026, 4:13 a.m. |
| PD | Predicate disambiguation | batch_69cd7c79f21c8190a7f31b2eab80b8ba |
completed | April 1, 2026, 8:13 p.m. |
Created at: March 30, 2026, 9:11 p.m.