Triple
T29757092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Governor Scott Buxton |
E753057
|
entity |
| Predicate | workAlsoReleasedInLanguage |
P11498
|
FINISHED |
| Object | Hindi |
—
|
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: Hindi | Statement: [Governor Scott Buxton, workAlsoReleasedInLanguage, Hindi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workAlsoReleasedInLanguage Context triple: [Governor Scott Buxton, workAlsoReleasedInLanguage, Hindi]
-
A.
languageOfReleases
chosen
Indicates the language in which the releases associated with an entity are produced or published.
-
B.
alsoWrittenIn
Indicates that the same content, work, or information is expressed or available in an additional language, script, or writing system.
-
C.
wroteInMultipleLanguages
Indicates that an entity authored written works using more than one language.
-
D.
alsoTranslatedAs
Indicates that something has an alternative translation or rendering in another language or form.
-
E.
adaptedInLanguage
Indicates that a work or content has been modified or translated so it can be presented or understood in a 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_69f0d62c84cc8190846f80ae04fdf8ec |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f673cbcbac819098e3b944b6fcfd1e |
completed | May 2, 2026, 9:59 p.m. |
| PD | Predicate disambiguation | batch_69f66ac1a4fc81909740d2e52fbe6970 |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 28, 2026, 7:57 p.m.