Triple
T19817236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 5th SS Panzer Division Wiking |
E476089
|
entity |
| Predicate | languageOfManyVolunteers |
P101585
|
FINISHED |
| Object | German |
—
|
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: German | Statement: [5th SS Panzer Division Wiking, languageOfManyVolunteers, German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfManyVolunteers Context triple: [5th SS Panzer Division Wiking, languageOfManyVolunteers, German]
-
A.
languageOfMembers
chosen
Indicates that the specified language is used or spoken by the members of a given group or organization.
-
B.
languagesSpoken
Indicates that an entity is able to communicate using one or more specified languages.
-
C.
eligibleLanguage
Indicates that a particular language satisfies the required conditions to be considered valid or allowed in a given context.
-
D.
estimatedNumberOfLanguages
Indicates the approximate count of distinct languages associated with an entity, typically based on estimation rather than an exact measurement.
-
E.
languageAdvocated
Indicates that an entity actively supports, promotes, or argues in favor of the use or adoption of a particular language.
- 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e654fac7b481909a19ae0d608e01d9 |
completed | April 20, 2026, 4:31 p.m. |
| PD | Predicate disambiguation | batch_69e5305858108190bbbfdb9ba3ab9f80 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:50 p.m.