Triple
T7520368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McDonald v. City of Chicago |
E177752
|
entity |
| Predicate | rightCharacterization |
P51828
|
FINISHED |
| Object | fundamental right |
—
|
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: fundamental right | Statement: [McDonald v. City of Chicago, rightCharacterization, fundamental right]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rightCharacterization Context triple: [McDonald v. City of Chicago, rightCharacterization, fundamental right]
-
A.
ruleCharacterization
Indicates that one rule is described, defined, or characterized in terms of another rule or set of rules.
-
B.
findingCharacterization
Indicates that a finding is being described or classified in terms of its nature, features, or diagnostic significance.
-
C.
resultCharacterization
Indicates how the outcome of an event, process, or action is qualitatively described or characterized.
-
D.
scopeCharacterization
chosen
Indicates how the extent, boundaries, or coverage of something is defined, described, or qualified in relation to another entity or context.
-
E.
characterizedBy
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
- 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_69c69f2891148190a484f3b8222c6f1b |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f5f98ae48190946a18d7c2d33bcd |
completed | March 27, 2026, 9:26 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d6bb808190bdd04499fd3bceb6 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:46 p.m.