Triple
T16151422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | R. James Blackshire |
E391916
|
entity |
| Predicate | caseCharacterization |
P97541
|
FINISHED |
| Object | landmark decision on housing discrimination and equal protection |
—
|
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: landmark decision on housing discrimination and equal protection | Statement: [R. James Blackshire, caseCharacterization, landmark decision on housing discrimination and equal protection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: caseCharacterization Context triple: [R. James Blackshire, caseCharacterization, landmark decision on housing discrimination and equal protection]
-
A.
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.
-
B.
resultCharacterization
Indicates how the outcome of an event, process, or action is qualitatively described or characterized.
-
C.
issueCharacterization
chosen
Indicates how an issue, problem, or case is categorized or described in terms of its nature, type, or defining attributes.
-
D.
ruleCharacterization
Indicates that one rule is described, defined, or characterized in terms of another rule or set of rules.
-
E.
scopeCharacterization
Indicates how the extent, boundaries, or coverage of something is defined, described, or qualified in relation to another entity or context.
- 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_69d87f1c65e48190aa2b4c472e9bafc4 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21d981950819087fdacc7879dca97 |
completed | April 17, 2026, 11:46 a.m. |
| PD | Predicate disambiguation | batch_69e1828abb608190a99d86bce1d77de2 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 5:01 a.m.