Triple
T696414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ashkenazi Jewish diaspora |
E13903
|
entity |
| Predicate | hasHistoricalVernacular |
P11719
|
FINISHED |
| Object | Yiddish |
—
|
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: Yiddish | Statement: [Ashkenazi Jewish diaspora, hasHistoricalVernacular, Yiddish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricalVernacular Context triple: [Ashkenazi Jewish diaspora, hasHistoricalVernacular, Yiddish]
-
A.
hasHistoricalOrigin
Indicates that something originated, was first established, or came into existence during a specific historical period or context.
-
B.
historicalLanguage
Indicates that one language is a historical or earlier form/ancestor of another language.
-
C.
historicallySpokenIn
Indicates that a language was used for spoken communication in a particular place or region during a past historical period.
-
D.
historicalLanguageStatus
Indicates that a language had a particular official, social, or functional status during a past historical period.
-
E.
hasLinguisticHeritage
chosen
Indicates that one entity possesses or is associated with the linguistic background, tradition, or ancestry of another entity.
- 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_69a493406c408190957eeec9048a8fb6 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a0c8055881909565ebde2be8fd7a |
completed | March 1, 2026, 8:25 p.m. |
| PD | Predicate disambiguation | batch_69a49d23e0a08190b08be9d1eff2a1bb |
completed | March 1, 2026, 8:10 p.m. |
Created at: March 1, 2026, 7:36 p.m.