Triple
T6196394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Law, University of Neuchâtel |
E138518
|
entity |
| Predicate | operatesInLanguageContext |
P54642
|
FINISHED |
| Object | francophone context |
—
|
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: francophone context | Statement: [Faculty of Law, University of Neuchâtel, operatesInLanguageContext, francophone context]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatesInLanguageContext Context triple: [Faculty of Law, University of Neuchâtel, operatesInLanguageContext, francophone context]
-
A.
hasLanguageContext
Indicates that an entity is associated with or interpreted within a specific language or linguistic context.
-
B.
languageOfOperation
Indicates the language in which an entity (such as a system, service, or process) primarily operates or functions.
-
C.
originalLanguageContext
Indicates the language in which something was first created or expressed, providing the original linguistic context for its content or meaning.
-
D.
usesLanguageRuntime
Indicates that an entity operates using, depends on, or is executed within a specific language runtime environment.
-
E.
languageOfInstitutionalContext
chosen
Indicates the language used as the primary medium of communication within an institutional setting or context.
- 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_69c008ab9b3081908a11b2c744838435 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062508f5c8190a00291708a9a7de9 |
completed | March 22, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69c055fbce1081908805fd12e242ab96 |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:20 p.m.