Triple
T24473823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quimper faience |
E617172
|
entity |
| Predicate | languageOfMarks |
P15804
|
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: [Quimper faience, languageOfMarks, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfMarks Context triple: [Quimper faience, languageOfMarks, French]
-
A.
languageOfLetters
Indicates that one entity is the language in which the other entity’s letters or written correspondence are composed.
-
B.
languageOfSignatures
Indicates the language in which the signatures on a document or agreement are written or expressed.
-
C.
languageOfNotation
Indicates the language in which a given notation, script, or symbolic system is expressed or encoded.
-
D.
inscriptionsLanguage
chosen
Indicates that the language used in the inscriptions on an object or surface is the specified language.
-
E.
languageOfManuscript
Indicates the language in which a given manuscript is written.
- 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_69e2d7f197588190889a03e620558059 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f299457ce081909e8d95fd482928dc |
completed | April 29, 2026, 11:50 p.m. |
| PD | Predicate disambiguation | batch_69f287d76c7c81909494f12e606a9149 |
completed | April 29, 2026, 10:36 p.m. |
Created at: April 18, 2026, 2:20 a.m.