Triple
T14001117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenneth Petty |
E336825
|
entity |
| Predicate | registeredSexOffender |
P80418
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Kenneth Petty, registeredSexOffender, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: registeredSexOffender Context triple: [Kenneth Petty, registeredSexOffender, true]
-
A.
criminalStatus
Indicates the legal condition of an entity with respect to criminal law, such as whether they are accused, convicted, or cleared of a crime.
-
B.
criminalRecord
chosen
Indicates that an entity has a documented history of criminal offenses or convictions recorded by an authority.
-
C.
convictedIndividual
Indicates that an individual has been found guilty of a crime or offense through a formal legal process and has received a conviction.
-
D.
associatedWithCrimeRecordOfUser
Indicates a relationship where something is linked to, or derived from, the crime record belonging to a specific user.
-
E.
consideredCriminalBy
Indicates that one party regards or classifies another party as a criminal according to its own laws, rules, or judgments.
- 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.