Triple
T11393145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States v. Anthony Russo |
E269896
|
entity |
| Predicate | classificationStatusOfDocuments |
P99074
|
FINISHED |
| Object | classified |
—
|
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: classified | Statement: [United States v. Anthony Russo, classificationStatusOfDocuments, classified]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: classificationStatusOfDocuments Context triple: [United States v. Anthony Russo, classificationStatusOfDocuments, classified]
-
A.
classificationLetter
Indicates that an entity is assigned a specific letter-based category or grade as its classification.
-
B.
classificationConsensus
Indicates that multiple agents or sources agree on the same classification or category assignment for a given entity or item.
-
C.
classified
Indicates that one entity has assigned another entity to a specific category, group, or type based on defined criteria.
-
D.
areClassifiedBy
Indicates that entities are assigned to one or more categories, types, or classes according to a specified classification scheme.
-
E.
recognizesDocument
Indicates that one entity acknowledges the validity or authenticity of a document associated with another entity.
- 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_69d6aacdbc6c8190af6dc3d5f5d22836 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d8001796f48190822526f52e3f0337 |
completed | April 9, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69d7e70b228c8190b87f5101fd683788 |
completed | April 9, 2026, 5:51 p.m. |
| PDg | Predicate description generation | batch_69d80010712c819089ea2e31e664abe1 |
completed | April 9, 2026, 7:37 p.m. |
Created at: April 8, 2026, 9:34 p.m.