Triple
T35662170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prix Vie heureuse |
E1030462
|
entity |
| Predicate | targetWorkLanguage |
P56541
|
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: [Prix Vie heureuse, targetWorkLanguage, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetWorkLanguage Context triple: [Prix Vie heureuse, targetWorkLanguage, French]
-
A.
targetsLanguage
Indicates that an action, resource, or entity is specifically directed toward, designed for, or intended to be used with a particular language.
-
B.
containsWorkLanguage
Indicates that one entity includes or is associated with a specific language used for a work (such as a document, publication, or creative piece).
-
C.
targetLanguage
chosen
Indicates the language that is the intended recipient or focus of a communication, translation, or linguistic operation.
-
D.
lenguaDeTrabajo
Indicates that something functions as a working language used for communication in a specific context or setting.
-
E.
workLanguageVariant
Indicates that one language variant of a work is related to another version of the same work, typically differing by language or localization.
- 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_69f76e09f87881909c954aaac176c34f |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fef112398081909237c3872345968b |
completed | May 9, 2026, 8:32 a.m. |
| PD | Predicate disambiguation | batch_69feefb14ec08190ab401987d8c84a23 |
completed | May 9, 2026, 8:26 a.m. |
Created at: May 3, 2026, 4:05 p.m.