Triple
T12808533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cantata III (Christmas Oratorio) |
E306206
|
entity |
| Predicate | originalLanguageOfText |
P5459
|
FINISHED |
| Object | German |
—
|
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: German | Statement: [Cantata III (Christmas Oratorio), originalLanguageOfText, German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalLanguageOfText Context triple: [Cantata III (Christmas Oratorio), originalLanguageOfText, German]
-
A.
originalTextLanguage
chosen
Indicates the language in which a text was originally written or created before any translation or adaptation.
-
B.
originalLanguageOfWholeWork
Indicates that a given language is the primary or original language in which an entire work (such as a book, film, or other complete creation) was first produced or expressed.
-
C.
originalLanguageAuthor
Indicates that an author created a work in a particular original language.
-
D.
originalLanguageContext
Indicates the language in which something was first created or expressed, providing the original linguistic context for its content or meaning.
-
E.
originalLanguageCountry
Indicates the country where a work’s original language is primarily spoken or officially used.
- 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_69d7bdf46c448190b1faa55aaacb6317 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e808130819080f404b3a7462c2e |
completed | April 10, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69d9640ed7448190b276e7fab649f7d2 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:31 p.m.