Triple
T10127270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karaim language |
E226245
|
entity |
| Predicate | subjectToLanguageShift |
P43833
|
FINISHED |
| Object | Lithuanian |
—
|
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: Lithuanian | Statement: [Karaim language, subjectToLanguageShift, Lithuanian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectToLanguageShift Context triple: [Karaim language, subjectToLanguageShift, Lithuanian]
-
A.
languageShift
Indicates a change in the primary language used by an entity, such as switching from one language to another over time or in a given context.
-
B.
languageAffected
Indicates that one entity has an impact on, modifies, or influences the characteristics, usage, or status of a language.
-
C.
languageShiftPressureFrom
chosen
Indicates pressure exerted by one entity that causes or encourages another entity to shift away from its current language toward a different language.
-
D.
hasCulturalShift
Indicates a change in the prevailing beliefs, values, norms, or practices within a group, organization, or society over time.
-
E.
focusesOnLanguage
Indicates that an entity’s primary attention, activity, or content is directed toward language as its main subject or concern.
- 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_69ca843057b48190a86730167f5d6b98 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cdd2eef7388190b95ffd02814f2d1f |
completed | April 2, 2026, 2:22 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba1d360819087698d04a53cc87e |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:05 p.m.