Triple
T671757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BBC Studios |
E12985
|
entity |
| Predicate | languageOfPrimaryOutput |
P18295
|
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: [BBC Studios, languageOfPrimaryOutput, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfPrimaryOutput Context triple: [BBC Studios, languageOfPrimaryOutput, 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.
standardLanguageOf
Indicates that one entity serves as the officially recognized or commonly used standard language for another entity (such as a country, region, or organization).
-
C.
nativeLanguage
Indicates the language that a person or entity originally learned and uses as their primary or first language.
-
D.
primaryLanguageOfInstruction
Indicates the language that is mainly used as the medium of teaching or instruction for a given educational context.
-
E.
languageOfExpression
Indicates that a particular language is used as the medium or form in which an expression (such as a text, utterance, or work) is realized.
- F. None of above. chosen
Provenance (4 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_69a493355dec819098d4244b2fa34885 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a1b3682c8190a9b9a454480c3446 |
completed | March 1, 2026, 8:29 p.m. |
| PD | Predicate disambiguation | batch_69a49d1a16c48190af89e3b078a4957e |
completed | March 1, 2026, 8:10 p.m. |
| PDg | Predicate description generation | batch_69a4a1b240648190bf15415205399d97 |
completed | March 1, 2026, 8:29 p.m. |
Created at: March 1, 2026, 7:36 p.m.