Triple
T25639939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lawrence Russell Brewer |
E642809
|
entity |
| Predicate | typeOfOffender |
P103759
|
FINISHED |
| Object | death row inmate |
—
|
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: death row inmate | Statement: [Lawrence Russell Brewer, typeOfOffender, death row inmate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfOffender Context triple: [Lawrence Russell Brewer, typeOfOffender, death row inmate]
-
A.
perpetratorType
chosen
Indicates the classification or category of the entity that carried out or is responsible for a harmful, illegal, or otherwise wrongful act.
-
B.
targetOffenderType
Indicates the specific category or type of offender that an action, rule, or condition is directed toward.
-
C.
roleInCrime
Indicates the specific function, responsibility, or participation an entity has within the commission of a particular crime.
-
D.
criminalType
Indicates the specific category or classification of crime associated with a criminal act or offender.
-
E.
perpetratorStatus
Indicates the role or condition of an individual in relation to committing or being responsible for a specific harmful or criminal act.
- 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_69e77e7ce28081908b08d65ee6e5c8be |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f72921cf2c8190909bb53f78bcc890 |
completed | May 3, 2026, 10:53 a.m. |
| PD | Predicate disambiguation | batch_69f7283d8cec8190b524c144948bc4ec |
completed | May 3, 2026, 10:49 a.m. |
Created at: April 21, 2026, 5:39 p.m.