Triple
T32888246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shnitzel |
E841261
|
entity |
| Predicate | vocabularyStyle |
P137145
|
FINISHED |
| Object | limited vocabulary |
—
|
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: limited vocabulary | Statement: [Shnitzel, vocabularyStyle, limited vocabulary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vocabularyStyle Context triple: [Shnitzel, vocabularyStyle, limited vocabulary]
-
A.
spellingStyle
Indicates the particular orthographic convention or system of spelling that is used or preferred in a given context.
-
B.
stylisticRange
Indicates the range or spectrum of styles that characterize or can be applied to something.
-
C.
stylisticFocus
Indicates a relationship where something is primarily concerned with, emphasizes, or is characterized by a particular style or set of stylistic features.
-
D.
styleLanguage
Indicates a relationship where one entity specifies the language or linguistic style in which another entity is expressed, formatted, or presented.
-
E.
stylisticElement
chosen
Indicates a relationship where one entity functions as a stylistic feature, device, or characteristic that shapes the expressive or aesthetic quality of another entity.
- 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_69f349446e288190a70c05bcc4d81172 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d16f5cb881908eed141afaaa0b51 |
completed | May 3, 2026, 4:39 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe45554819089cbbd538d992132 |
completed | May 3, 2026, 4:32 a.m. |
Created at: May 1, 2026, 1:18 a.m.