Triple
T30227236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Studio Green |
E768518
|
entity |
| Predicate | distributesInLanguage |
P3681
|
FINISHED |
| Object | Tamil |
—
|
NE NERFINISHED |
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: Tamil | Statement: [Studio Green, distributesInLanguage, Tamil]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distributesInLanguage Context triple: [Studio Green, distributesInLanguage, Tamil]
-
A.
distributesIn
Indicates that one entity allocates or hands out something (e.g., items, resources, information) within or across a specified area, group, or context.
-
B.
hasLanguageInCountry
Indicates that a particular language is used or recognized within a specified country.
-
C.
isScheduledLanguageOf
Indicates that a particular language is officially planned or designated to be used for a specific event, program, or context.
-
D.
isLanguageOf
Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
-
E.
presentedInLanguage
chosen
Indicates that something (such as content, information, or a work) is expressed or made available using a particular 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_69f2248108208190be60bf1af343ce70 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6d0d46aec819091edf97324d793ac |
completed | May 3, 2026, 4:36 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe2183481908ae4e85a59c66f69 |
completed | May 3, 2026, 4:32 a.m. |
Created at: April 29, 2026, 7:36 p.m.