Triple
T37582096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Princesse de Clèves (1961 film) |
E934997
|
entity |
| Predicate | workBasedOnGenre |
P29867
|
FINISHED |
| Object | French classic literature |
—
|
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 classic literature | Statement: [La Princesse de Clèves (1961 film), workBasedOnGenre, French classic literature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workBasedOnGenre Context triple: [La Princesse de Clèves (1961 film), workBasedOnGenre, French classic literature]
-
A.
basedOnWorkGenre
chosen
Indicates that one entity’s genre classification is derived from or determined by the genre of another work.
-
B.
workBasedOnFilm
Indicates that a creative work is derived from, adapted from, or otherwise based on a particular film.
-
C.
workedOnGenre
Indicates that an entity (such as a person or organization) has done work related to a particular genre.
-
D.
workNumberInGenre
Indicates the ordinal position or sequence number assigned to a particular work within a specific genre.
-
E.
hasGenreOfWorkItAppearsIn
Indicates that an entity is associated with the genre of the work in which it appears.
- 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_69f76ece61dc8190a0ab33f8d87d0a7e |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbb084760c8190a1554985d3c3cb7a |
completed | May 6, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_69fbadf3cb548190ba3b7514f76b790a |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:17 p.m.