Triple
T34970274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aurora Leigh |
E1008515
|
entity |
| Predicate | influencesThemeInWork |
P151748
|
FINISHED |
| Object | critique of philanthropy |
—
|
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: critique of philanthropy | Statement: [Aurora Leigh, influencesThemeInWork, critique of philanthropy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influencesThemeInWork Context triple: [Aurora Leigh, influencesThemeInWork, critique of philanthropy]
-
A.
influencesThemeOf
chosen
Indicates that one entity affects, shapes, or contributes to the thematic content or underlying message of another entity.
-
B.
associatedWithWorkTheme
Indicates a relationship where something is connected or related to a particular work theme or subject matter.
-
C.
influencedWorkType
Indicates that one work has affected or shaped the type, category, or form of another work.
-
D.
influencedWork
Indicates that one work has had a significant impact on the creation, style, content, or development of another work.
-
E.
hasOccupationTheme
Indicates that something (such as a work or resource) centrally involves or focuses on a particular occupation or type of work as its main theme.
- 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_69f76dc78a308190a1ac29ad4a9a4895 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd3a69f1e08190a11aed015bff0858 |
completed | May 8, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69fd39124180819080ca7911d3515d6d |
completed | May 8, 2026, 1:14 a.m. |
Created at: May 3, 2026, 4 p.m.