Triple
T2323793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Law Division (Circuit Court of Cook County) |
E48239
|
entity |
| Predicate | typicalReliefSought |
P2242
|
FINISHED |
| Object | monetary damages |
—
|
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: monetary damages | Statement: [Law Division (Circuit Court of Cook County), typicalReliefSought, monetary damages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalReliefSought Context triple: [Law Division (Circuit Court of Cook County), typicalReliefSought, monetary damages]
-
A.
remedySought
chosen
Indicates that a particular legal or corrective action is being requested as a solution or relief in response to a problem or dispute.
-
B.
reliefGranted
Indicates that a requested form of assistance, exemption, or remedy has been officially approved and provided.
-
C.
relievedBy
Indicates that one entity eases, reduces, or removes the burden, pain, stress, or responsibility experienced by another entity.
-
D.
hasRelief
Indicates that one entity features or exhibits a raised or sculpted surface design (relief) in relation to another entity or context.
-
E.
typeOfClaim
Indicates the specific category or nature of a claim being made in relation to an entity or statement.
- 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_69a88aa308a88190b0b86c011fda7fce |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc685f05481909c863b29d1f6bacd |
completed | March 7, 2026, 6:32 a.m. |
| PD | Predicate disambiguation | batch_69abc5909cc48190aab257313542dc49 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.