Triple
T8763069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cinderella (fairy tale) |
E208251
|
entity |
| Predicate | firstWellKnownLiteraryVersionYear |
P85246
|
FINISHED |
| Object | 1697 |
—
|
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: 1697 | Statement: [Cinderella (fairy tale), firstWellKnownLiteraryVersionYear, 1697]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstWellKnownLiteraryVersionYear Context triple: [Cinderella (fairy tale), firstWellKnownLiteraryVersionYear, 1697]
-
A.
firstPublishedInWorkYear
Indicates the year in which a work was first published.
-
B.
firstEnglishTranslationYear
Indicates the year in which an entity was first translated into English.
-
C.
firstEditionPublicationYear
Indicates the year in which an entity’s first edition was originally published.
-
D.
firstCompletePublicationYear
Indicates the calendar year in which an entity’s first complete publication was released.
-
E.
firstAssociatedPublicationYear
Indicates the calendar year in which an entity’s earliest associated publication was first released or made publicly available.
- 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_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. |
| PDg | Predicate description generation | batch_69cc5cfddef48190aee764ee7b25bae9 |
completed | March 31, 2026, 11:47 p.m. |
Created at: March 30, 2026, 6:40 p.m.