Triple
T2311807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sup Ct |
E51974
|
entity |
| Predicate | courtTypeReferredTo |
P8214
|
FINISHED |
| Object | court of general jurisdiction |
—
|
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: court of general jurisdiction | Statement: [Sup Ct, courtTypeReferredTo, court of general jurisdiction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: courtTypeReferredTo Context triple: [Sup Ct, courtTypeReferredTo, court of general jurisdiction]
-
A.
hasTypeOfCourt
chosen
Indicates that an entity is associated with or classified by a specific type or category of court.
-
B.
affectedCourt
Indicates that a particular court is impacted or influenced by a specified action, decision, or legal matter.
-
C.
courtContext
Indicates the legal or judicial setting, circumstances, or framework within which a court-related action or relationship takes place.
-
D.
usedCourt
Indicates that an entity made use of or participated in legal proceedings within a particular court.
-
E.
trialCourt
Indicates that a legal matter, decision, or proceeding is associated with, handled by, or occurring in a court of first instance (the trial-level court).
- 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_69a88b0bb30c81908ded03b006d29387 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc685f05481909c863b29d1f6bacd |
completed | March 7, 2026, 6:32 a.m. |
| PD | Predicate disambiguation | batch_69abc58e88e481908733fdf79d3f8a15 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.