Triple
T11536074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mutterzunge |
E273550
|
entity |
| Predicate | literaryLanguageFeature |
P6520
|
FINISHED |
| Object | mixing of Turkish and 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: mixing of Turkish and German | Statement: [Mutterzunge, literaryLanguageFeature, mixing of Turkish and German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literaryLanguageFeature Context triple: [Mutterzunge, literaryLanguageFeature, mixing of Turkish and German]
-
A.
literaryFeature
Indicates a relationship where something possesses or exhibits a characteristic, device, or stylistic element used in literature.
-
B.
literaryLanguage
Indicates that an entity is expressed, written, or communicated using a particular literary or standardized written language.
-
C.
linguisticFeature
chosen
Indicates a relationship where a linguistic property, pattern, or characteristic is attributed to or associated with a language-related entity (such as a word, phrase, or text).
-
D.
literaryScript
Indicates a relationship where an entity serves as the written text or script of a literary work, such as a play, film, or other narrative production.
-
E.
languageCharacterizedBy
Indicates that a language is defined or distinguished by a particular feature, property, or characteristic.
- 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_69d6aae3fbec8190a14632a5df2538b6 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8839b4bb48190b748ec4119f36c11 |
completed | April 10, 2026, 4:59 a.m. |
| PD | Predicate disambiguation | batch_69d80879fdb48190be6dacc8aa63c809 |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:37 p.m.