Triple
T1243663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marion Wiesel |
E26714
|
entity |
| Predicate | languagePair |
P25926
|
FINISHED |
| Object | French-to-English literary translation |
—
|
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-to-English literary translation | Statement: [Marion Wiesel, languagePair, French-to-English literary translation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languagePair Context triple: [Marion Wiesel, languagePair, French-to-English literary translation]
-
A.
languageProvision
Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
-
B.
languageBranch
Indicates that one language belongs to, or is classified under, a broader linguistic branch or subgroup.
-
C.
languageShift
Indicates a change in the primary language used by an entity, such as switching from one language to another over time or in a given context.
-
D.
languageForm
Indicates the specific linguistic form or expression in which something is conveyed or represented.
-
E.
languageVariant
Indicates that one language is a variant, dialect, or localized form of another language.
- F. None of above. chosen
Provenance (4 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_69a4948689d08190b3a4a3f388c02148 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf636e208190a4d56806db61916c |
completed | March 1, 2026, 10:36 p.m. |
| PD | Predicate disambiguation | batch_69a4bb696a38819095845c84f0241287 |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bce611ec819092cb13d354d0903e |
completed | March 1, 2026, 10:25 p.m. |
Created at: March 1, 2026, 7:47 p.m.