Triple
T17294055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aaron Greidinger |
E419858
|
entity |
| Predicate | workOriginallyPublishedInLanguage |
P74798
|
FINISHED |
| Object | Yiddish |
—
|
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: Yiddish | Statement: [Aaron Greidinger, workOriginallyPublishedInLanguage, Yiddish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workOriginallyPublishedInLanguage Context triple: [Aaron Greidinger, workOriginallyPublishedInLanguage, Yiddish]
-
A.
originalLanguageOfWholeWork
chosen
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.
-
B.
originalLanguagePublisher
Indicates that a publisher is responsible for releasing a work in its original language, before or apart from any translations.
-
C.
originalPublicationLanguageVariant
Indicates that one language is a specific variant or version of the language in which a work was originally published.
-
D.
originalLanguageAuthor
Indicates that an author created a work in a particular original language.
-
E.
publicationLanguageOfSourceWork
Indicates the language in which the original source work was published.
- 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_69d886db32608190a61e18862c5a8af6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e437869ec08190b4a63fb1ee6a71ee |
completed | April 19, 2026, 2:01 a.m. |
| PD | Predicate disambiguation | batch_69e3b0118ad08190b119cd219c68ba67 |
completed | April 18, 2026, 4:23 p.m. |
Created at: April 10, 2026, 5:40 a.m.