Triple
T34250532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vézinet |
E878726
|
entity |
| Predicate | characterInWorkLanguage |
P71694
|
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: [Vézinet, characterInWorkLanguage, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterInWorkLanguage Context triple: [Vézinet, characterInWorkLanguage, French]
-
A.
isCharacterInWorkLanguage
chosen
Indicates that a character appears in a work (e.g., book, film, game) in a specific language version or localization.
-
B.
originalLanguageOfCharacterWork
Indicates that a language is the original language in which a particular character-related work (e.g., story, script, or media) was created or first expressed.
-
C.
characterInWorkDescribedAs
Indicates that a character is portrayed or described in a particular way within a specific work.
-
D.
basedOnCharacterFromWork
Indicates that one entity is derived from, inspired by, or modeled after a character that appears in another creative work.
-
E.
characterIn
Indicates that an entity appears as a character within a specified work, story, or narrative.
- 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_69f349b3618481909df955b063f305b2 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff63e6b61081909c648bf0ff279481 |
completed | May 9, 2026, 4:42 p.m. |
| PD | Predicate disambiguation | batch_69ff6381867881908ae0545df4b71df5 |
completed | May 9, 2026, 4:40 p.m. |
Created at: May 1, 2026, 1:56 a.m.