Triple
T25639942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lawrence Russell Brewer |
E642809
|
entity |
| Predicate | crimeLocationType |
P59762
|
FINISHED |
| Object | rural road near Jasper, Texas |
—
|
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: rural road near Jasper, Texas | Statement: [Lawrence Russell Brewer, crimeLocationType, rural road near Jasper, Texas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crimeLocationType Context triple: [Lawrence Russell Brewer, crimeLocationType, rural road near Jasper, Texas]
-
A.
crimeLocation
chosen
Indicates that a crime occurred at, or is associated with, a particular location.
-
B.
criminalType
Indicates the specific category or classification of crime associated with a criminal act or offender.
-
C.
regionOfCrimes
Indicates the geographic area or jurisdiction in which the crimes occurred or are attributed to an entity.
-
D.
crimeType
Indicates the specific category or nature of the crime associated with an event or entity.
-
E.
crimeRate
Indicates the frequency or level of criminal activity occurring within a given area or population.
- 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_69f600c18a14819081b5914dd3b0f9cf |
completed | May 2, 2026, 1:48 p.m. |
| PD | Predicate disambiguation | batch_69f5f7fba5248190945acf1561280799 |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 21, 2026, 5:39 p.m.