Triple
T11430219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruskin v. Whistler libel case |
E270858
|
entity |
| Predicate | highlightedTensionBetween |
P61198
|
FINISHED |
| Object | avant-garde 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: avant-garde art | Statement: [Ruskin v. Whistler libel case, highlightedTensionBetween, avant-garde art]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: highlightedTensionBetween Context triple: [Ruskin v. Whistler libel case, highlightedTensionBetween, avant-garde art]
-
A.
tension
Indicates a state of strain, stress, or conflict existing between entities, often involving opposing forces, interests, or emotions.
-
B.
hasTension
chosen
Indicates the presence of strain, stress, or conflict between entities in their relationship or interaction.
-
C.
tensionArea
Indicates the region or extent over which mechanical or emotional tension is distributed or experienced.
-
D.
languageTension
Indicates a relationship where differing languages or language use create conflict, strain, or friction between entities.
-
E.
diplomaticTensionBetween
Indicates a strained or conflict-prone diplomatic relationship existing between two entities.
- 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_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. |
Created at: April 8, 2026, 9:35 p.m.