Triple
T538600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Little Street |
E12379
|
entity |
| Predicate | hasDepictionType |
P9800
|
FINISHED |
| Object | outdoor scene |
—
|
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: outdoor scene | Statement: [The Little Street, hasDepictionType, outdoor scene]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDepictionType Context triple: [The Little Street, hasDepictionType, outdoor scene]
-
A.
depictionType
chosen
Indicates the specific manner or style in which something is visually represented or depicted.
-
B.
hasIllustrationsBy
Indicates that one entity (such as a work or publication) includes illustrations that were created by another entity (the illustrator).
-
C.
depictsMedium
Indicates that one entity visually represents or portrays the medium or material of another entity.
-
D.
depicts
Indicates that one entity visually represents, portrays, or shows another entity.
-
E.
depictsNationality
Indicates that one entity visually represents or portrays the nationality or national identity 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_69a4933208e88190891f5debab1b776d |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4985e51908190a34aa82ea9dbee1e |
completed | March 1, 2026, 7:49 p.m. |
| PD | Predicate disambiguation | batch_69a494b51ff08190a39f4168fd9a7ddf |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.