Triple
T34867670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NXIVM |
E1005056
|
entity |
| Predicate | criminalPractice |
P181945
|
FINISHED |
| Object | coercion |
—
|
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: coercion | Statement: [NXIVM, criminalPractice, coercion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: criminalPractice Context triple: [NXIVM, criminalPractice, coercion]
-
A.
legalPractice
Indicates a relationship where an entity engages in or is associated with the professional provision of legal services or the practice of law.
-
B.
legalSchoolPractice
Indicates that a particular legal practice, method, or approach is characteristic of, endorsed by, or derived from a specific school or tradition of law.
-
C.
practicedLawIn
Indicates that a person engaged in the professional practice of law within a specified jurisdiction or location.
-
D.
legalDevelopment
Indicates the occurrence or progression of a change, action, or event within a legal context, such as new laws, rulings, or regulatory updates affecting legal status or practice.
-
E.
criminalSpecialization
Indicates that an individual focuses their criminal activity on a particular type of offense or crime category.
- 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_69f76dbb678081909a247b9b5e1a73ac |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782f4f10081908f97f6d0d2dbeec7 |
completed | May 3, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69f780ff71cc8190a67e71076fbad81a |
completed | May 3, 2026, 5:08 p.m. |
| PDg | Predicate description generation | batch_69f782f416c081908bdd9b1ad456f0e2 |
completed | May 3, 2026, 5:16 p.m. |
Created at: May 3, 2026, 4 p.m.