Triple
T410039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York Supreme Court |
E9467
|
entity |
| Predicate | canGrant |
P2246
|
FINISHED |
| Object | injunctive relief |
—
|
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: injunctive relief | Statement: [New York Supreme Court, canGrant, injunctive relief]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canGrant Context triple: [New York Supreme Court, canGrant, injunctive relief]
-
A.
canEnforce
Indicates that one entity has the authority or capability to compel compliance with rules, decisions, or obligations upon another entity.
-
B.
grantedTo
Indicates that a right, permission, or resource has been formally given or assigned by one party to another.
-
C.
grantedBy
chosen
Indicates that a right, permission, or benefit is conferred or authorized by one entity to another.
-
D.
isGrantedFor
Indicates that a permission, right, or benefit has been formally given to a specific entity for a particular purpose or use.
-
E.
canMake
Indicates that one entity has the ability or capacity to create, produce, or assemble 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_69a2e80111fc8190961d5b7c6154123f |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ed31681c8190ac32334562fb17fd |
completed | Feb. 28, 2026, 1:27 p.m. |
| PD | Predicate disambiguation | batch_69a2e9737694819080fde9adcc1aa4d4 |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.