Triple
T8763079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cinderella (fairy tale) |
E208251
|
entity |
| Predicate | languageOfFirstPerraultVersion |
P29379
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [Cinderella (fairy tale), languageOfFirstPerraultVersion, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfFirstPerraultVersion Context triple: [Cinderella (fairy tale), languageOfFirstPerraultVersion, French]
-
A.
originalLanguageOfLibretto
Indicates the language in which a libretto was originally written for a given work.
-
B.
languageOfOfficialEditions
Indicates the language in which the official editions or versions of a work, document, or publication are produced or authorized.
-
C.
firstEditionLanguage
chosen
Indicates the language in which a work was originally published in its first edition.
-
D.
originalPublicationLanguageVariant
Indicates that one language is a specific variant or version of the language in which a work was originally published.
-
E.
languageOfParentWork
Indicates that the specified language is the language in which the parent (original or containing) work is expressed.
- 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_69ca835df7e08190ac875664cca8f9ca |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5dfc85e481909a7ce80c5022e6e9 |
completed | March 31, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1884bc8190a46e8308db31f7ab |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:40 p.m.