Triple
T138337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Painted Ladies (San Francisco) |
E2796
|
entity |
| Predicate | hasColorScheme |
P60
|
FINISHED |
| Object | multicolored facades |
—
|
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: multicolored facades | Statement: [Painted Ladies (San Francisco), hasColorScheme, multicolored facades]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasColorScheme Context triple: [Painted Ladies (San Francisco), hasColorScheme, multicolored facades]
-
A.
colors
chosen
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
B.
hasLiturgicalColor
Indicates that something is associated with a specific liturgical color used in religious rites or ceremonies.
-
C.
hasStyle
Indicates that an entity possesses, exhibits, or is characterized by a particular style or manner.
-
D.
hasFlowerColor
Indicates that an entity (typically a plant or flower) possesses a specific flower color.
-
E.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257a800148190be119d1d075869b8 |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a25652efdc8190b85b33735a9e6370 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.