Triple
T31530428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alberto Beddini |
E804461
|
entity |
| Predicate | culturalStereotypeUsed |
P181769
|
FINISHED |
| Object | comic Italian designer |
—
|
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: comic Italian designer | Statement: [Alberto Beddini, culturalStereotypeUsed, comic Italian designer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: culturalStereotypeUsed Context triple: [Alberto Beddini, culturalStereotypeUsed, comic Italian designer]
-
A.
notableStereotype
Indicates that a commonly recognized stereotype is associated with the subject in relation to the object.
-
B.
hasRacialStereotypes
Indicates that one entity portrays, attributes, or associates racial stereotypes with another entity.
-
C.
culturallyPerceivedAs
Indicates that one entity is regarded or interpreted in a particular way by a culture or cultural group.
-
D.
usedCulture
Indicates that one entity employed, applied, or drew upon the cultural practices, norms, or artifacts associated with another entity.
-
E.
usedInCulture
Indicates that something (such as an object, practice, or concept) is employed, referenced, or plays a role within a particular culture or cultural context.
- F. None of above. chosen
Provenance (4 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_69f348d03ef88190a2b73d7b94b9e02d |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f7824dc3f0819092a5102895b4a478 |
completed | May 3, 2026, 5:13 p.m. |
| PD | Predicate disambiguation | batch_69f780fc5ed88190b7200ee5a29940af |
completed | May 3, 2026, 5:08 p.m. |
| PDg | Predicate description generation | batch_69f7817c79e081908e685c48165e086b |
completed | May 3, 2026, 5:10 p.m. |
Created at: April 30, 2026, 10:01 p.m.