Triple
T15103165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Otto Delaney |
E360719
|
entity |
| Predicate | incarcerationReason |
P3353
|
FINISHED |
| Object | violent crimes |
—
|
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: violent crimes | Statement: [Otto Delaney, incarcerationReason, violent crimes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: incarcerationReason Context triple: [Otto Delaney, incarcerationReason, violent crimes]
-
A.
hasReasonForArrest
Indicates that an arrest is associated with a specific reason or cause.
-
B.
imprisonedFor
chosen
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.
-
C.
reasonForConviction
Indicates the specific offense or legal basis for which an individual was found guilty or convicted.
-
D.
arrestedFor
Indicates that an authority has taken someone into custody because they are suspected or accused of committing a specified offense or wrongdoing.
-
E.
reasonForPunishment
Indicates that one entity is the cause, justification, or grounds for another entity receiving a punishment.
- 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_69d85a0491ec8190830960be8fafb994 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00551521c8190b48d1a074bb4bdfc |
completed | April 15, 2026, 9:38 p.m. |
| PD | Predicate disambiguation | batch_69deb96c1d9c81909351558ed97bc5b7 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:05 a.m.