Triple
T12336231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Dickens |
E294091
|
entity |
| Predicate | influenceOnWork |
P1994
|
FINISHED |
| Object | portrayal of debtors in Charles Dickens's fiction |
—
|
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: portrayal of debtors in Charles Dickens's fiction | Statement: [John Dickens, influenceOnWork, portrayal of debtors in Charles Dickens's fiction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influenceOnWork Context triple: [John Dickens, influenceOnWork, portrayal of debtors in Charles Dickens's fiction]
-
A.
workImpact
Indicates that one entity’s work has an effect or influence on another entity, situation, or outcome.
-
B.
influencedWork
chosen
Indicates that one work has had a significant impact on the creation, style, content, or development of another work.
-
C.
reflectsOnWork
Indicates that an entity engages in thoughtful consideration or evaluation of their own work or work-related activities.
-
D.
workRelatedTo
Indicates a relationship where one entity’s work, tasks, or professional activities are connected, associated, or relevant to those of another entity.
-
E.
appliedWork
Indicates that an entity has put effort, skill, or labor into performing or producing a particular work or task.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f6683e881908920e1fee02a14e3 |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ecb5efc819086a3530282278bb1 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:53 p.m.