Triple
T6905042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Introduction à l'étude de la médecine expérimentale |
E159791
|
entity |
| Predicate | langue |
P18209
|
FINISHED |
| Object | français |
—
|
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: français | Statement: [Introduction à l'étude de la médecine expérimentale, langue, français]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: langue Context triple: [Introduction à l'étude de la médecine expérimentale, langue, français]
-
A.
partOfLanguage
Indicates that one linguistic element belongs to, is included within, or is a component of a particular language.
-
B.
languageUse
chosen
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
C.
deFactoLanguage
Indicates that a language is used in practice as the primary or common language in a context, even if it has no official legal status there.
-
D.
languageForm
Indicates the specific linguistic form or expression in which something is conveyed or represented.
-
E.
lexifierLanguage
Indicates that one language serves as the primary source or base language from which the core vocabulary and structure of another language, typically a pidgin or creole, are derived.
- 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_69c68839ccb88190b4aa5cc1aca3448f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d98b07f0819093595e958fa0317b |
completed | March 27, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b7681481909ec50509b19fcf81 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:25 p.m.