Triple
T25632668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Volonté de savoir |
E642613
|
entity |
| Predicate | seriesTitleInFrench |
P71619
|
FINISHED |
| Object | Histoire de la sexualité |
—
|
NE NERFINISHED |
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: Histoire de la sexualité | Statement: [La Volonté de savoir, seriesTitleInFrench, Histoire de la sexualité]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seriesTitleInFrench Context triple: [La Volonté de savoir, seriesTitleInFrench, Histoire de la sexualité]
-
A.
equivalentTitleInFrench
Indicates that one entity’s title is the equivalent or corresponding title of another entity, specifically expressed in French.
-
B.
titleInLanguage
Indicates that a specific title or name is expressed in a particular language.
-
C.
isTitleSeriesOf
Indicates that one entity is the title or name associated with a particular series (such as a book, film, or media franchise).
-
D.
languageOfSeries
Indicates the language in which a series is primarily produced, presented, or officially released.
-
E.
seriesTitleElement
chosen
Indicates that the value represents a component or segment of the title of a series to which a resource belongs.
- 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_69e77e7bd4548190a0c691b8a2f27ff1 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f650c70d7c819093d9a0f005f7c8d5 |
completed | May 2, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69f64cab1f648190a2a9460690d18a37 |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 21, 2026, 5:19 p.m.