Triple
T12960560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maître Derville |
E310130
|
entity |
| Predicate | languageOfCharacterName |
P15
|
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: [Maître Derville, languageOfCharacterName, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfCharacterName Context triple: [Maître Derville, languageOfCharacterName, French]
-
A.
languageOfWorkOrName
chosen
Indicates the language in which a work is created or a name is expressed.
-
B.
languageOfHonoredFigure
Indicates the language associated with or used by the person who is being honored.
-
C.
languageSpokenOnScreen
Indicates that a particular language is used in spoken dialogue or audible communication within an on-screen work (such as a film, show, or video).
-
D.
languageOfLetters
Indicates that one entity is the language in which the other entity’s letters or written correspondence are composed.
-
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_69d7bdfb57a88190836b743e2825feca |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97dba57988190b786ffed55687a72 |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 5:44 p.m.