Triple
T20879199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Public Enemy No. 1 (FBI label for John Dillinger) |
E514098
|
entity |
| Predicate | appliedToCrimeType |
P7957
|
FINISHED |
| Object | armed robbery |
—
|
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: armed robbery | Statement: [Public Enemy No. 1 (FBI label for John Dillinger), appliedToCrimeType, armed robbery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliedToCrimeType Context triple: [Public Enemy No. 1 (FBI label for John Dillinger), appliedToCrimeType, armed robbery]
-
A.
crimeType
chosen
Indicates the specific category or nature of the crime associated with an event or entity.
-
B.
recognitionOfCrimes
Indicates the formal acknowledgment or identification that certain actions or events constitute crimes under a legal or normative framework.
-
C.
committedCrime
Indicates that an entity has carried out or been responsible for a criminal act or offense.
-
D.
hasCrimeElement
Indicates that a situation, action, or entity involves or contains a component that is legally recognized as part of a crime.
-
E.
pursuesCrimeType
Indicates that an entity (such as a law enforcement body or individual) actively investigates, targets, or prosecutes a specified type of 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_69e0b4f733f081908a401c0b7beb0b9f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c678b394819096a17de9e04cd74f |
completed | April 21, 2026, 12:36 a.m. |
| PD | Predicate disambiguation | batch_69e5c9a8dc148190b33ff51894e2a8f9 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:45 p.m.