Triple
T13654612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rocket Docket |
E326824
|
entity |
| Predicate | impactOnDefendants |
P110997
|
FINISHED |
| Object | less time to prepare defenses |
—
|
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: less time to prepare defenses | Statement: [Rocket Docket, impactOnDefendants, less time to prepare defenses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnDefendants Context triple: [Rocket Docket, impactOnDefendants, less time to prepare defenses]
-
A.
impactOnLaw
Indicates the effect or influence that one entity, event, or action has on laws, legal rules, or the legal system.
-
B.
impactOnLawEnforcement
Indicates the effect or consequences that something has on law enforcement activities, operations, or effectiveness.
-
C.
impactOnCaseFlow
Indicates how an event, action, or decision affects the progression, timing, or movement of cases through a process or system.
-
D.
impactOnDirector
Indicates that one entity has an effect, influence, or consequence on a director in the context of a given situation or action.
-
E.
hasDefendants
Indicates that one or more entities serve as defendants in relation to a particular legal case or proceeding.
- F. None of above. chosen
Provenance (4 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_69d8076d8270819092afc2f0e9c359a8 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc60ace048190a4b92310ba272bd1 |
completed | April 12, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69dbbe8a027081908d8f884b89707a5e |
completed | April 12, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69dbc59ca1a88190a6abd3bd00554c93 |
completed | April 12, 2026, 4:17 p.m. |
Created at: April 9, 2026, 9:52 p.m.