Triple
T26323462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sylvana |
E662180
|
entity |
| Predicate | typicalLanguageContext |
P42338
|
FINISHED |
| Object | European languages |
—
|
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: European languages | Statement: [Sylvana, typicalLanguageContext, European languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLanguageContext Context triple: [Sylvana, typicalLanguageContext, European languages]
-
A.
typicalLanguages
chosen
Indicates the languages that are commonly or characteristically used, spoken, or associated with a given entity.
-
B.
typicalLanguageUse
Indicates that one entity is the language most commonly or habitually used by another entity in ordinary communication or contexts.
-
C.
languageOfSurroundingCulture
Indicates that one entity is the language predominantly used or characteristic of the surrounding culture associated with another entity.
-
D.
nativeLanguageContext
Indicates the relationship in which a language functions as the primary or native linguistic context for an entity’s communication or interpretation.
-
E.
languageOfInstitutionalContext
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_69ee812e73048190aae587f1d51e5a06 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69fe744faca881908e11e90e0a35653f |
completed | May 8, 2026, 11:39 p.m. |
| PD | Predicate disambiguation | batch_69fe734cbf7081909a552c5cf3b5ea59 |
completed | May 8, 2026, 11:35 p.m. |
Created at: April 26, 2026, 10:29 p.m.