Triple
T21049831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Volksgerichtshof |
E518546
|
entity |
| Predicate | trialLanguage |
P142640
|
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: [Volksgerichtshof, trialLanguage, German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trialLanguage Context triple: [Volksgerichtshof, trialLanguage, German]
-
A.
testLanguage
Indicates that an entity uses or is associated with a particular language for testing or evaluation purposes.
-
B.
linguisticTarget
Indicates that something serves as the specific linguistic element (such as a word, phrase, or expression) that is the focus or target of a given action, analysis, or relation.
-
C.
eligibleLanguage
Indicates that a particular language satisfies the required conditions to be considered valid or allowed in a given context.
-
D.
possibleLanguage
Indicates that an entity could plausibly be expressed, interpreted, or communicated in a given language.
-
E.
languageIntroduced
Indicates that a particular language was brought into use or made known within a certain context, time, or place.
- F. None of above. chosen
Provenance (4 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_69e0b5053ac48190921529544959e906 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fd7a5cf48190939aefaa44db1ddb |
completed | April 21, 2026, 4:30 a.m. |
| PD | Predicate disambiguation | batch_69e5dbf6728881908a2a43a5c8804a2a |
completed | April 20, 2026, 7:55 a.m. |
| PDg | Predicate description generation | batch_69e5e2df1a888190b5b478e76bdf7fdf |
completed | April 20, 2026, 8:25 a.m. |
Created at: April 16, 2026, 2:34 p.m.