Triple
T12735673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Albert Francis "Sonny" Capone |
E304355
|
entity |
| Predicate | criminal record |
P80418
|
FINISHED |
| Object | minor offenses |
—
|
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: minor offenses | Statement: [Albert Francis "Sonny" Capone, criminal record, minor offenses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: criminal record Context triple: [Albert Francis "Sonny" Capone, criminal record, minor offenses]
-
A.
criminalRecord
chosen
Indicates that an entity has a documented history of criminal offenses or convictions recorded by an authority.
-
B.
criminalStatus
Indicates the legal condition of an entity with respect to criminal law, such as whether they are accused, convicted, or cleared of a crime.
-
C.
associatedWithCrimeRecordOfUser
Indicates a relationship where something is linked to, or derived from, the crime record belonging to a specific user.
-
D.
convictedOf
Indicates that a person or entity has been found guilty of committing a specified offense or crime through a formal legal process.
-
E.
crimeCharged
Indicates that legal authorities have formally accused an entity of committing a specific crime.
- 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_69d7bdf1426c8190a4402e1c4cdec33a |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d89ea70819098c470344f172167 |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96403957c81909acdee7bdae71696 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:26 p.m.