Triple
T14001115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenneth Petty |
E336825
|
entity |
| Predicate | hasConviction |
P90191
|
FINISHED |
| Object | attempted rape |
—
|
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: attempted rape | Statement: [Kenneth Petty, hasConviction, attempted rape]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasConviction Context triple: [Kenneth Petty, hasConviction, attempted rape]
-
A.
convictedOf
Indicates that a person or entity has been found guilty of committing a specified offense or crime through a formal legal process.
-
B.
hasHadCriminalConviction
chosen
Indicates that an entity has previously been found guilty of a criminal offense through a legal process.
-
C.
hasFirstConviction
Indicates that an entity has received its first legal conviction for an offense.
-
D.
convictedBy
Indicates that an authority, typically a court or judge, has formally found an entity guilty of a crime or offense.
-
E.
numberOfConvictions
Indicates the count of times an entity has been formally found guilty of an 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_69d81c645c5c8190b1fd16a285a1b78a |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2ed06a50819093ddc64f55050689 |
completed | April 14, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_69dd465dfbc4819090d8c61fd572d35f |
completed | April 13, 2026, 7:39 p.m. |
Created at: April 9, 2026, 10:19 p.m.