Triple
T5663366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portrait of Dora Wheeler |
E124796
|
entity |
| Predicate | hasBackdropDescription |
P15585
|
FINISHED |
| Object | ornate decorative pattern |
—
|
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: ornate decorative pattern | Statement: [Portrait of Dora Wheeler, hasBackdropDescription, ornate decorative pattern]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBackdropDescription Context triple: [Portrait of Dora Wheeler, hasBackdropDescription, ornate decorative pattern]
-
A.
formsBackdropOf
Indicates that one entity serves as the background or setting against which another entity is viewed, occurs, or is presented.
-
B.
hasBackground
chosen
Indicates that an entity possesses or is associated with a particular background, such as context, setting, or prior circumstances.
-
C.
hasDescription
Indicates that an entity is associated with a textual description that explains or characterizes it.
-
D.
backedFor
Indicates that one entity provides support, endorsement, or backing for another entity, often in a financial, political, or strategic context.
-
E.
hasBackrestType
Indicates the specific kind or style of backrest that an object (typically a seat or chair) possesses.
- 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_69c00828906881908966f270b8f130cf |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0236d3f94819095111c41a323612d |
completed | March 22, 2026, 5:14 p.m. |
| PD | Predicate disambiguation | batch_69c021ba4ec481909db8cdbf0e907dd6 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:43 p.m.