Triple
T11430228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruskin v. Whistler libel case |
E270858
|
entity |
| Predicate | typeOfDefamation |
P99262
|
FINISHED |
| Object | printed review |
—
|
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: printed review | Statement: [Ruskin v. Whistler libel case, typeOfDefamation, printed review]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfDefamation Context triple: [Ruskin v. Whistler libel case, typeOfDefamation, printed review]
-
A.
typeOfDefense
Indicates the specific kind or category of defense employed or possessed in a given context.
-
B.
litigationType
Indicates the specific category or nature of a legal dispute or court case associated with an entity or event.
-
C.
accusationType
Indicates the specific category or nature of an accusation made by one party against another.
-
D.
definitionType
Indicates the specific kind or category of definition that characterizes how one entity is defined in relation to another.
-
E.
controversyType
Indicates the specific kind or category of controversy associated with an entity or situation.
- F. None of above. chosen
Provenance (4 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_69d6aadeef688190874bcecd88b3dd9b |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d806c1bfb881909720c74fe0fa837f |
completed | April 9, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69d7e71436f88190ac7e45a04ea5c987 |
completed | April 9, 2026, 5:51 p.m. |
| PDg | Predicate description generation | batch_69d80010712c819089ea2e31e664abe1 |
completed | April 9, 2026, 7:37 p.m. |
Created at: April 8, 2026, 9:35 p.m.