Triple
T30845577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boulevard des Capucines (Monet) |
E785622
|
entity |
| Predicate | original language of title |
P3048
|
FINISHED |
| Object | French |
—
|
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 | Statement: [Boulevard des Capucines (Monet), original language of title, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: original language of title Context triple: [Boulevard des Capucines (Monet), original language of title, French]
-
A.
originalLanguageTitle
Indicates the title of a work as it appears in its original language of creation or publication.
-
B.
originalTitleLanguage
chosen
Indicates the language in which a work’s original title was written or expressed.
-
C.
originalLanguageOfFilmOrTVShow
Indicates the language in which a film or TV show was originally produced and released.
-
D.
originalLanguageText
Indicates that a text is expressed in its original, untranslated language.
-
E.
originalTitleName
Indicates that one entity is the original or primary title name associated with another entity.
- 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_69f224b850848190a4af4ccf8ddadcdf |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a00708ab11081909641d245c4282aa0 |
completed | May 10, 2026, 11:48 a.m. |
| PD | Predicate disambiguation | batch_6a00703daa0081908903ce3a28084d35 |
completed | May 10, 2026, 11:47 a.m. |
Created at: April 29, 2026, 8:46 p.m.