Triple
T14670365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madame Pichon |
E344493
|
entity |
| Predicate | authorWorkLanguage |
P74740
|
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: [Madame Pichon, authorWorkLanguage, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: authorWorkLanguage Context triple: [Madame Pichon, authorWorkLanguage, French]
-
A.
publicationLanguageOfSourceWork
Indicates the language in which the original source work was published.
-
B.
languageOfParentWork
Indicates that the specified language is the language in which the parent (original or containing) work is expressed.
-
C.
originalLanguageOfWholeWork
Indicates that a given language is the primary or original language in which an entire work (such as a book, film, or other complete creation) was first produced or expressed.
-
D.
languageOfWritings
Indicates that a specified language is the one in which certain writings or written works are composed.
-
E.
originalLanguageAuthor
chosen
Indicates that an author created a work in a particular original 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_69d822e283fc8190a0e4c235cf880052 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb54ef2908190b189ced65eec434a |
completed | April 14, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69de6576f0208190aa94d995e797ac38 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:27 a.m.