Triple
T29587183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L’Âme en fleur |
E754050
|
entity |
| Predicate | isContainedInNumberOfBooks |
P5478
|
FINISHED |
| Object | 1 (Les Contemplations) |
—
|
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: 1 (Les Contemplations) | Statement: [L’Âme en fleur, isContainedInNumberOfBooks, 1 (Les Contemplations)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isContainedInNumberOfBooks Context triple: [L’Âme en fleur, isContainedInNumberOfBooks, 1 (Les Contemplations)]
-
A.
intendedNumberOfBooks
Indicates the number of books that an agent plans or aims to have, produce, read, or otherwise be associated with, as opposed to the number actually realized.
-
B.
containsBook
chosen
Indicates that one entity (typically a container or collection) includes a specific book as part of its contents.
-
C.
numberOfBooks
Indicates the quantity of books associated with a given entity.
-
D.
bookNumberInCollection
Indicates the specific numerical position assigned to a book within a particular collection.
-
E.
hasNumberOfBooksInSeries
Indicates the quantity of books that belong to a particular series.
- 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_69f0ef836ac88190bd809dc58b5ec907 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f6b2a65c7c8190ac40f1466ceadefc |
completed | May 3, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f6b14d7d508190bc7d4c89dfba4a32 |
completed | May 3, 2026, 2:22 a.m. |
Created at: April 28, 2026, 6:11 p.m.