Triple
T739443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Darwin (civil servant) |
E15209
|
entity |
| Predicate | criminalPenalty |
P8398
|
FINISHED |
| Object | 6 years and 3 months 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: 6 years and 3 months imprisonment | Statement: [John Darwin (civil servant), criminalPenalty, 6 years and 3 months imprisonment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: criminalPenalty Context triple: [John Darwin (civil servant), criminalPenalty, 6 years and 3 months imprisonment]
-
A.
crimeType
Indicates the specific category or nature of the crime associated with an event or entity.
-
B.
convictedOf
Indicates that a person or entity has been found guilty of committing a specified offense or crime through a formal legal process.
-
C.
durationOfImprisonment
chosen
Indicates the length of time that an entity is or was held in imprisonment.
-
D.
imprisonedFor
Indicates that one entity is held in detention or jail as a consequence of, or in connection with, a specific reason, action, or offense committed by another entity or itself.
-
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_69a49358aa308190adbc9b5a0a2adcf9 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a64adf2c81908e48090be35dd9d9 |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a4fc734c81908fbd36386d5746d6 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.