Triple
T7010689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theuerdank |
E162571
|
entity |
| Predicate | typography |
P42388
|
FINISHED |
| Object | Fraktur type |
—
|
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: Fraktur type | Statement: [Theuerdank, typography, Fraktur type]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typography Context triple: [Theuerdank, typography, Fraktur type]
-
A.
typographer
Indicates that an entity is a person or agent whose role is to design, arrange, or set type for printed or digital text.
-
B.
typographicLegacy
Indicates a relationship where one typographic style, convention, or feature is inherited from, derived from, or historically influenced by another.
-
C.
hasTypography
chosen
Indicates that one entity uses, is associated with, or is characterized by a particular typographic style, font, or text layout.
-
D.
typographicRole
Indicates the specific typographic function or role that an element plays within written or printed content.
-
E.
textType
Indicates the classification of a text according to its type, format, or genre.
- 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_69c6885928148190ae31909fbb5e9849 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dc3917c481909a288c3e56630c48 |
completed | March 27, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c790288190b7cbbaa4a5f9c91d |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:34 p.m.