Triple
T968371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Café Terrace at Night |
E20888
|
entity |
| Predicate | original title language |
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: [Café Terrace at Night, original title language, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: original title language Context triple: [Café Terrace at Night, original title language, 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.
originalTitleOfWork
Indicates that one work is the original title under which another work was first created, published, or released.
-
D.
originallyTitleOf
Indicates that one title is the original title from which another work, edition, or localized title is derived.
-
E.
titleInEnglish
Indicates that an entity’s title or name is given in the English language.
- 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_69a493b33d2c81909c52c369d3ca8436 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b4481f508190adcf0a965a23862c |
completed | March 1, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a579888190afb489ac9fe8391c |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.