Triple
T7059175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Book VI (Disquisitiones Arithmeticae) |
E164170
|
entity |
| Predicate | originalLanguageOfWholeWork |
P74798
|
FINISHED |
| Object | Latin |
—
|
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: Latin | Statement: [Book VI (Disquisitiones Arithmeticae), originalLanguageOfWholeWork, Latin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalLanguageOfWholeWork Context triple: [Book VI (Disquisitiones Arithmeticae), originalLanguageOfWholeWork, Latin]
-
A.
originalLanguageCountry
Indicates the country where a work’s original language is primarily spoken or officially used.
-
B.
originalLanguageOfFilmOrTVShow
Indicates the language in which a film or TV show was originally produced and released.
-
C.
originalLanguagePublisher
Indicates that a publisher is responsible for releasing a work in its original language, before or apart from any translations.
-
D.
languageOfParentWork
Indicates that the specified language is the language in which the parent (original or containing) work is expressed.
-
E.
originalLanguageTitle
Indicates the title of a work as it appears in its original language of creation or publication.
- 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_69c68861678881909961ddf4d779f750 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e4a3c36c819080942c59f1830ae8 |
completed | March 27, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bdc1f08190975fcdbbb1854d1e |
completed | March 27, 2026, 7:59 p.m. |
| PDg | Predicate description generation | batch_69c6e4a15b088190bee9a23e94aaac53 |
completed | March 27, 2026, 8:12 p.m. |
Created at: March 27, 2026, 2:38 p.m.