Triple
T1623896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Academy of Arts |
E35092
|
entity |
| Predicate | hasInfluenceArea |
P2828
|
FINISHED |
| Object | British art |
—
|
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: British art | Statement: [Royal Academy of Arts, hasInfluenceArea, British art]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInfluenceArea Context triple: [Royal Academy of Arts, hasInfluenceArea, British art]
-
A.
affectedArea
Indicates the specific region or extent over which an event, condition, or influence has an impact.
-
B.
hasAreaOfInterest
Indicates that an entity possesses or is associated with a particular area of interest or focus.
-
C.
sphereOfInfluence
chosen
Indicates the area or domain within which an entity exerts significant control, impact, or authority over others.
-
D.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
E.
hasLandmarkArea
Indicates that a specified area is designated as the landmark area associated with a particular entity or location.
- 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_69a886023194819080a3fccd6e325d0e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aaf4a0ef748190ae52b9656474c0ef |
completed | March 6, 2026, 3:37 p.m. |
| PD | Predicate disambiguation | batch_69a907c731808190a1d998155041b3c1 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.