Triple
T9953809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luigi’s Pizza |
E195394
|
entity |
| Predicate | hasDepictionStyle |
P9800
|
FINISHED |
| Object | cartoon |
—
|
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: cartoon | Statement: [Luigi’s Pizza, hasDepictionStyle, cartoon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDepictionStyle Context triple: [Luigi’s Pizza, hasDepictionStyle, cartoon]
-
A.
canBeDepictedAs
Indicates that one entity is capable of being visually represented or illustrated in the form or style of another entity.
-
B.
depictionType
chosen
Indicates the specific manner or style in which something is visually represented or depicted.
-
C.
depictsAttribute
Indicates that one entity visually represents or illustrates a specific attribute or characteristic of another entity.
-
D.
artisticDepiction
Indicates that one entity visually represents, portrays, or illustrates another in an artistic medium.
-
E.
depictionDetail
Indicates that one depiction provides additional detail, refinement, or a closer view of what is shown in another depiction.
- 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_69ca82eaaa008190a54fa1a9f954b9ad |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb694b95481909d049302818e7137 |
completed | April 2, 2026, 12:21 a.m. |
| PD | Predicate disambiguation | batch_69cd1d97c44081908730071269f07712 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:46 p.m.