Triple
T28923932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vera Claythorne |
E733592
|
entity |
| Predicate | motiveForCrime |
P65261
|
FINISHED |
| Object | to enable Hugo Hamilton to inherit money |
—
|
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: to enable Hugo Hamilton to inherit money | Statement: [Vera Claythorne, motiveForCrime, to enable Hugo Hamilton to inherit money]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: motiveForCrime Context triple: [Vera Claythorne, motiveForCrime, to enable Hugo Hamilton to inherit money]
-
A.
reasonForMurder
Indicates the motive or underlying cause that led someone to commit a murder.
-
B.
hasMotiveOfCriminals
chosen
Indicates that the specified motive is attributed to or associated with the criminals in question.
-
C.
depictsMotive
Indicates that one entity visually represents or illustrates the motive, intention, or underlying reason associated with another entity or action.
-
D.
reasonForConviction
Indicates the specific offense or legal basis for which an individual was found guilty or convicted.
-
E.
methodOfMurderScheme
Indicates the specific method or scheme by which a murder is carried out in a given situation or plan.
- 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_69f05b0a5cc0819094828367ae204b70 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c2198208190a3954086c22cfcbf |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, 8:22 a.m.