Triple
T13677973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Old Fritz |
E327924
|
entity |
| Predicate | referentPrimaryLanguage |
P83252
|
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: [The Old Fritz, referentPrimaryLanguage, German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: referentPrimaryLanguage Context triple: [The Old Fritz, referentPrimaryLanguage, German]
-
A.
primaryLanguageOf
Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
-
B.
primaryLanguageIn
Indicates that a specified language is the main or official language used within a particular place, organization, or context.
-
C.
hasPrimaryLanguage1
chosen
Indicates that an entity’s main or most commonly used language is the specified language.
-
D.
primaryLanguageType
Indicates the main category or kind of language (such as spoken, written, or signed) that serves as the primary mode of communication in a given context or for a given entity.
-
E.
primaryLanguageSide1
Indicates that the specified language is the main or dominant language associated with the first participant or side in a relationship.
- 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_69d8076f1fa8819094664a59b55010df |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc65d8dc081909664e69bb38610ba |
completed | April 12, 2026, 4:20 p.m. |
| PD | Predicate disambiguation | batch_69dbbe8d8d0881908d6e89954f44eed4 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:53 p.m.