Triple
T939242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilhelm Keppler |
E20265
|
entity |
| Predicate | convictionPenalty |
P20881
|
FINISHED |
| Object | 10 years imprisonment |
—
|
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: 10 years imprisonment | Statement: [Wilhelm Keppler, convictionPenalty, 10 years imprisonment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: convictionPenalty Context triple: [Wilhelm Keppler, convictionPenalty, 10 years imprisonment]
-
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.
placeOfConviction
Indicates the location where a person was formally convicted of a crime or offense.
-
C.
dateOfConviction
Indicates the specific calendar date on which a person or entity was formally found guilty of an offense.
-
D.
numberOfConvictions
Indicates the count of times an entity has been formally found guilty of an offense.
-
E.
sentencedTo
chosen
Indicates that an authority has officially assigned a specific punishment or penalty to an entity, typically as the outcome of a legal or disciplinary process.
- 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_69a493b0270c81909e6c9ce310f6aa55 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b38a3ad4819080d71849e822a12a |
completed | March 1, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69a4b29c68f48190aecad10e351a99de |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.