Triple
T29032716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anthony Marston |
E737769
|
entity |
| Predicate | showsRemorseForCrime |
P125251
|
FINISHED |
| Object | no |
—
|
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: no | Statement: [Anthony Marston, showsRemorseForCrime, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: showsRemorseForCrime Context triple: [Anthony Marston, showsRemorseForCrime, no]
-
A.
repentsFor
chosen
Indicates that one entity feels remorse or regret for an action, wrongdoing, or harm related to another entity.
-
B.
repentedIn
Indicates that an entity has expressed remorse or regret for its actions within a particular context, time, or situation.
-
C.
penance
Indicates an act of self-imposed suffering, discipline, or reparation performed to atone for a wrongdoing or moral failing.
-
D.
contritionType
Indicates the specific kind or category of contrition (remorse or repentance) associated with an action or state.
-
E.
guiltyOf
Indicates that an entity has been judged or determined to have committed a particular offense, crime, or wrongful act.
- 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_69f077ef00fc81909325f084ad37c035 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f674e06c9481909ed0ea736408f0d7 |
completed | May 2, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69f673c4abec8190bc2379e66f4af0a9 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 28, 2026, 9:56 a.m.