Triple
T8206292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mishenka |
E191695
|
entity |
| Predicate | baseNameLanguageOfOrigin |
P28203
|
FINISHED |
| Object | Hebrew |
—
|
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: Hebrew | Statement: [Mishenka, baseNameLanguageOfOrigin, Hebrew]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: baseNameLanguageOfOrigin Context triple: [Mishenka, baseNameLanguageOfOrigin, Hebrew]
-
A.
hasLanguageOfOrigin
Indicates that one entity has its origin or source in the language specified by another entity.
-
B.
originalNameLanguage
chosen
Indicates that the specified language is the language in which an entity’s original or primary name was expressed.
-
C.
hasEndonymLanguage
Indicates that the language specified is the one in which a name or term is expressed in its own native or local form.
-
D.
nativeLanguage
Indicates the language that a person or entity originally learned and uses as their primary or first language.
-
E.
primaryLanguageOf
Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
- 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_69ca82c7f3e08190857bf1fc63b2a10c |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb726b520081908ce4a03bd14dfcdf |
completed | March 31, 2026, 7:06 a.m. |
| PD | Predicate disambiguation | batch_69cb36ad01ac81909609b15f6a6c8581 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:43 p.m.