Triple
T6361519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crime and Punishment |
E143119
|
entity |
| Predicate | hasCrime |
P65441
|
FINISHED |
| Object | murder of a pawnbroker |
—
|
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: murder of a pawnbroker | Statement: [Crime and Punishment, hasCrime, murder of a pawnbroker]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCrime Context triple: [Crime and Punishment, hasCrime, murder of a pawnbroker]
-
A.
hasCrimeElement
chosen
Indicates that a situation, action, or entity involves or contains a component that is legally recognized as part of a crime.
-
B.
haveCriminalLaw
Indicates that an entity possesses, applies, or is governed by a system or body of criminal law.
-
C.
committedCrime
Indicates that an entity has carried out or been responsible for a criminal act or offense.
-
D.
convictedOf
Indicates that a person or entity has been found guilty of committing a specified offense or crime through a formal legal process.
-
E.
hasCrimeInvestigation
Indicates that an entity is the subject of, or associated with, a formal investigation into a crime.
- 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_69c008d7a9c4819098d647ec47776917 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c067fa0d0c819098d01545849142fc |
completed | March 22, 2026, 10:06 p.m. |
| PD | Predicate disambiguation | batch_69c060ec091c8190912aac44e1b8b1c9 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:32 p.m.