Triple
T15156930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Screws v. United States |
E362102
|
entity |
| Predicate | standardCharacterization |
P116954
|
FINISHED |
| Object | narrow interpretation of willfulness requirement |
—
|
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: narrow interpretation of willfulness requirement | Statement: [Screws v. United States, standardCharacterization, narrow interpretation of willfulness requirement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: standardCharacterization Context triple: [Screws v. United States, standardCharacterization, narrow interpretation of willfulness requirement]
-
A.
sourceCharacterization
Indicates that one entity describes, explains, or characterizes the origin, provenance, or source of another entity.
-
B.
initialCharacterization
Indicates the first or earliest formal description, assessment, or classification made about an entity or situation.
-
C.
resultCharacterization
Indicates how the outcome of an event, process, or action is qualitatively described or characterized.
-
D.
studyCharacterization
Indicates a relationship where an entity conducts a detailed examination or analysis to characterize or define the properties, behavior, or features of another entity.
-
E.
ruleCharacterization
Indicates that one rule is described, defined, or characterized in terms of another rule or set of rules.
- 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_69d85a0759908190b8a051d2e2a1cbe6 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0060c62b08190bcdbd912d011d1ba |
completed | April 15, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69deb9779acc81908ed2dad382c42dca |
completed | April 14, 2026, 10:02 p.m. |
| PDg | Predicate description generation | batch_69dec72059c08190a34f513a00185b08 |
completed | April 14, 2026, 11 p.m. |
Created at: April 10, 2026, 3:08 a.m.