Triple
T9466268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Studio 8G |
E228277
|
entity |
| Predicate | primaryLanguageOfProductions |
P1252
|
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: [Studio 8G, primaryLanguageOfProductions, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryLanguageOfProductions Context triple: [Studio 8G, primaryLanguageOfProductions, English]
-
A.
primaryLanguageOf
chosen
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.
languageOfPrimaryNarrations
Indicates the language in which the main or primary narrations are expressed or conveyed.
-
D.
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).
-
E.
hasPrimaryLanguage1
Indicates that an entity’s main or most commonly used language is the specified language.
- 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_69ca846fee388190a6ec273fd644b88b |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7fdc08f08190ad17de08d2c2eca2 |
completed | April 1, 2026, 8:28 p.m. |
| PD | Predicate disambiguation | batch_69cca55caaa8819089c5138e014892d3 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:53 p.m.