Triple
T1917287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth Siddal |
E40045
|
entity |
| Predicate | RuskinStipend |
P2134
|
FINISHED |
| Object | annual stipend to support her 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: annual stipend to support her art | Statement: [Elizabeth Siddal, RuskinStipend, annual stipend to support her art]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: RuskinStipend Context triple: [Elizabeth Siddal, RuskinStipend, annual stipend to support her art]
-
A.
scholarshipType
chosen
Indicates the specific category or kind of scholarship associated with an entity.
-
B.
hasHonoraryDegreeFrom
Indicates that an individual has been awarded an honorary degree by a particular institution.
-
C.
awardFor
Indicates that something is given or granted as recognition or a prize for a particular achievement, work, or contribution.
-
D.
isMajorAwardIn
Indicates that an award is considered a major or highly significant award within a specified context, such as a field, event, or organization.
-
E.
awardScope
Indicates the extent, domain, or coverage that an award applies to within a given context.
- 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_69a8864298748190a2f2fd34f7ef8d77 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb2107fe48190bafff825f1f805ad |
completed | March 7, 2026, 5:05 a.m. |
| PD | Predicate disambiguation | batch_69abafed2ab481908920334e77b1021b |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:35 p.m.