Triple
T32805244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Der Doppelgänger |
E839003
|
entity |
| Predicate | firstLanguageOfText |
P5459
|
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: [Der Doppelgänger, firstLanguageOfText, German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstLanguageOfText Context triple: [Der Doppelgänger, firstLanguageOfText, German]
-
A.
originalTextLanguage
chosen
Indicates the language in which a text was originally written or created before any translation or adaptation.
-
B.
primaryLanguageOfTranslation
Indicates that a given language is the main or principal language into which something has been translated.
-
C.
primaryLanguageOf
Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
-
D.
primaryLanguageAnalyzed
Indicates that the specified language is the main or principal language used for analysis in the given context.
-
E.
mainLanguageOf
Indicates that a specified language is the primary or dominant language used by a particular entity (such as a person, document, or organization).
- 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_69f3493d35208190b4351b4e85f2fa16 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:15 a.m.