Triple
T33272193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anthony Bottom |
E851803
|
entity |
| Predicate | legalStatusAfterConviction |
P121935
|
FINISHED |
| Object | incarcerated for several decades |
—
|
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: incarcerated for several decades | Statement: [Anthony Bottom, legalStatusAfterConviction, incarcerated for several decades]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalStatusAfterConviction Context triple: [Anthony Bottom, legalStatusAfterConviction, incarcerated for several decades]
-
A.
legalStatusAtConviction
Indicates the legal status or condition an individual held at the time they were convicted.
-
B.
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.
-
C.
legalStatusBeforeRelease
Indicates the legal condition or classification an entity was subject to prior to its release.
-
D.
legalStatusAfterEvent
chosen
Indicates the legal condition or classification an entity has as a result of a specified event or occurrence.
-
E.
convictedOf
Indicates that a person or entity has been found guilty of committing a specified offense or crime through a formal legal 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_69f349642dac81908a37ffcc3b976a55 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69ff1f3f94fc819095955299f50ab4ce |
completed | May 9, 2026, 11:49 a.m. |
| PD | Predicate disambiguation | batch_69ff1ea47748819082f63d9b9d9c3e65 |
completed | May 9, 2026, 11:46 a.m. |
Created at: May 1, 2026, 1:32 a.m.