Triple
T33598049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alex Lippi |
E860629
|
entity |
| Predicate | filmTitleInFrench |
P89513
|
FINISHED |
| Object | L’Arnacoeur |
—
|
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: L’Arnacoeur | Statement: [Alex Lippi, filmTitleInFrench, L’Arnacoeur]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmTitleInFrench Context triple: [Alex Lippi, filmTitleInFrench, L’Arnacoeur]
-
A.
film4Title
Indicates that the specified title is the fourth film title associated with the given entity or within a particular ordered sequence of films.
-
B.
film6Title
Indicates the title assigned to the sixth film in a sequence or collection.
-
C.
equivalentTitleInFrench
Indicates that one entity’s title is the equivalent or corresponding title of another entity, specifically expressed in French.
-
D.
titleInLanguage
chosen
Indicates that a specific title or name is expressed in a particular language.
-
E.
sourceFilmTitle
Indicates the title of the film from which a referenced work, element, or derivative content originates.
- 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_69f3497f35908190a2e9bbb9b96c7a3f |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f7a6486c8190811ecf3ea5fedba5 |
completed | May 3, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_69f6f6632dfc8190af85e258c8519207 |
completed | May 3, 2026, 7:16 a.m. |
Created at: May 1, 2026, 1:41 a.m.