Triple
T16151624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York Criminal Anarchy Law |
E391922
|
entity |
| Predicate | enforcementFocus |
P66945
|
FINISHED |
| Object | radical political activists |
—
|
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: radical political activists | Statement: [New York Criminal Anarchy Law, enforcementFocus, radical political activists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: enforcementFocus Context triple: [New York Criminal Anarchy Law, enforcementFocus, radical political activists]
-
A.
enforcement
Indicates the act of compelling compliance with rules, laws, or agreements through monitoring, pressure, or sanctions.
-
B.
enforcementStrength
Indicates the degree or intensity with which rules, laws, or policies are applied and enforced in a given context.
-
C.
focusesOn
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
D.
statutoryFocus
chosen
Indicates that something is the primary subject, concern, or area of emphasis specified or governed by a statute or legal provision.
-
E.
enforcementModel
Indicates the method or framework by which rules, policies, or constraints are applied, monitored, and enforced within a system or interaction.
- 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_69d87f1c65e48190aa2b4c472e9bafc4 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21d981950819087fdacc7879dca97 |
completed | April 17, 2026, 11:46 a.m. |
| PD | Predicate disambiguation | batch_69e1828abb608190a99d86bce1d77de2 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 5:01 a.m.