Triple
T23780461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dmytrii |
E587797
|
entity |
| Predicate | linguisticUsageRegion |
P29819
|
FINISHED |
| Object | Eastern Europe |
—
|
NE NERFINISHED |
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: Eastern Europe | Statement: [Dmytrii, linguisticUsageRegion, Eastern Europe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linguisticUsageRegion Context triple: [Dmytrii, linguisticUsageRegion, Eastern Europe]
-
A.
linguisticUsage
Indicates how a linguistic form, expression, or construction is used in language, such as its typical context, function, or register.
-
B.
languageArea
chosen
Indicates the geographic or cultural region in which a particular language is used or predominantly spoken.
-
C.
regionOfMajorLanguage
Indicates the geographic region where a particular language is predominantly spoken or holds major usage.
-
D.
alsoInLanguageRegion
Indicates that two or more entities are located within or associated with the same language-defined geographic region.
-
E.
linguisticArea
Indicates a regional context in which languages share features due to geographic proximity and contact rather than common genetic origin.
- 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_69e2490d245881909028226a1393d624 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1c62bef608190b75afa6bf4024ae3 |
completed | April 29, 2026, 8:49 a.m. |
| PD | Predicate disambiguation | batch_69f155f79e34819080f9ddb972b34deb |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:16 p.m.