Triple
T21149774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles Workman |
E521156
|
entity |
| Predicate | typeOfCriminal |
P96742
|
FINISHED |
| Object | mob hitman |
—
|
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: mob hitman | Statement: [Charles Workman, typeOfCriminal, mob hitman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfCriminal Context triple: [Charles Workman, typeOfCriminal, mob hitman]
-
A.
criminalType
chosen
Indicates the specific category or classification of crime associated with a criminal act or offender.
-
B.
roleInCrime
Indicates the specific function, responsibility, or participation an entity has within the commission of a particular crime.
-
C.
perpetratorType
Indicates the classification or category of the entity that carried out or is responsible for a harmful, illegal, or otherwise wrongful act.
-
D.
crimeType
Indicates the specific category or nature of the crime associated with an event or entity.
-
E.
committedCrime
Indicates that an entity has carried out or been responsible for a criminal act or offense.
- 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_69e0b50c6a848190a4e525a77a319b8a |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e72400911c8190978e88138a9bfaff |
completed | April 21, 2026, 7:15 a.m. |
| PD | Predicate disambiguation | batch_69e5f5f8a5bc819081918c7fa8e4496d |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 2:58 p.m.