Triple
T8831513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ginger and Fred |
E210154
|
entity |
| Predicate | hasVisualReference |
P77199
|
FINISHED |
| Object | curving façade of Dancing House |
—
|
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: curving façade of Dancing House | Statement: [Ginger and Fred, hasVisualReference, curving façade of Dancing House]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVisualReference Context triple: [Ginger and Fred, hasVisualReference, curving façade of Dancing House]
-
A.
hasVisualIndicator
Indicates that an entity is associated with some form of visual cue or marker that signals its status, condition, or presence.
-
B.
visualizedIn
chosen
Indicates that something is represented or depicted within a particular visual medium, view, or visualization.
-
C.
hasColorReference
Indicates that one entity serves as a reference or source for determining or specifying the color associated with another entity.
-
D.
hasView
Indicates that one entity provides a visual perspective or outlook onto another entity or scene.
-
E.
isReferencePointFor
Indicates that one entity serves as a positional or conceptual basis used to locate, measure, or interpret 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_69ca8365b28081909e48e45e95dfc405 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc604ed2b88190b4f53b34b5a438f7 |
completed | April 1, 2026, 12:01 a.m. |
| PD | Predicate disambiguation | batch_69cc5c23d08481908d8c9b0ad3d1dc00 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:47 p.m.