Triple
T33497222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Légendes et chansons de gestes canaques |
E857894
|
entity |
| Predicate | literaryAdaptation |
P184408
|
FINISHED |
| Object | French literary style |
—
|
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 literary style | Statement: [Légendes et chansons de gestes canaques, literaryAdaptation, French literary style]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literaryAdaptation Context triple: [Légendes et chansons de gestes canaques, literaryAdaptation, French literary style]
-
A.
filmAdaptationOfWork
Indicates that a film is an adaptation based on the narrative content of a specific original work.
-
B.
inFilmAdaptation
Indicates that one work or element appears within, or is incorporated into, a film adaptation of another work.
-
C.
bookAdaptedInto
Indicates that a book has been turned into another work, typically in a different medium such as a film, TV series, or play.
-
D.
musicalAdaptationBy
Indicates that one work has been adapted into a musical by a specified creator or adapter.
-
E.
notableAdaptationType
Indicates that one work is a significant adaptation of another work in a specific way or medium (e.g., film adaptation, stage adaptation).
- 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_69f3497660508190a541826a81f7e9ab |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7b0e5744c8190a22c1e1d6fcfa466 |
completed | May 3, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f7ab70d034819080295628497d8582 |
completed | May 3, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69f7b0e3917481908a394680d76743c3 |
completed | May 3, 2026, 8:32 p.m. |
Created at: May 1, 2026, 1:38 a.m.