Triple
T29820178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kurban Said |
E757222
|
entity |
| Predicate | workOriginalLanguagePublicationYear |
P168687
|
FINISHED |
| Object | German edition 1937 |
—
|
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 edition 1937 | Statement: [Kurban Said, workOriginalLanguagePublicationYear, German edition 1937]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workOriginalLanguagePublicationYear Context triple: [Kurban Said, workOriginalLanguagePublicationYear, German edition 1937]
-
A.
workInOriginalLanguage
Indicates that a work is being created, presented, or studied in the language in which it was originally produced, without translation.
-
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.
originalTitleLanguage
Indicates the language in which a work’s original title was written or expressed.
-
E.
originalLanguageCountry
Indicates the country where a work’s original language is primarily spoken or officially used.
- 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_69f2245701c88190ad42415a0956c4ed |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f67595fa7c8190b6e9f7a8c700dd97 |
completed | May 2, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69f673c4abec8190bc2379e66f4af0a9 |
completed | May 2, 2026, 9:59 p.m. |
| PDg | Predicate description generation | batch_69f674df80b08190adb7f7531083bbb1 |
completed | May 2, 2026, 10:04 p.m. |
Created at: April 29, 2026, 5:28 p.m.