Triple
T16999950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carlos de Austria |
E412414
|
entity |
| Predicate | cultureDepiction |
P18272
|
FINISHED |
| Object | subject of Friedrich Schiller's play "Don Carlos" |
—
|
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: subject of Friedrich Schiller's play "Don Carlos" | Statement: [Carlos de Austria, cultureDepiction, subject of Friedrich Schiller's play "Don Carlos"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cultureDepiction Context triple: [Carlos de Austria, cultureDepiction, subject of Friedrich Schiller's play "Don Carlos"]
-
A.
cultureDepicted
Indicates that one entity portrays, represents, or is associated with the culture of another entity.
-
B.
culturalDepictionBy
Indicates that one entity serves as the creator or source of a cultural representation or portrayal of another entity.
-
C.
hasCulturalDepiction
chosen
Indicates that one entity is represented, portrayed, or depicted in the cultural work or expression of another entity.
-
D.
cultureCharacteristic
Indicates that a particular trait, practice, or feature is a defining characteristic of a given culture.
-
E.
media depiction
Indicates that one entity visually or narratively represents, portrays, or illustrates another entity in some form of media.
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d37d9f9081909aef52426d88940d |
completed | April 18, 2026, 6:54 p.m. |
| PD | Predicate disambiguation | batch_69e35d552bc08190af17ef7659e094ef |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:32 a.m.