Triple
T24209745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ole "Swede" Andersen |
E600498
|
entity |
| Predicate | murderTriggers |
P155216
|
FINISHED |
| Object | investigation into his past |
—
|
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: investigation into his past | Statement: [Ole "Swede" Andersen, murderTriggers, investigation into his past]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: murderTriggers Context triple: [Ole "Swede" Andersen, murderTriggers, investigation into his past]
-
A.
murders
Indicates that one entity unlawfully and intentionally kills another entity.
-
B.
hasMurderer
Indicates that one entity is the person who committed the murder of another entity.
-
C.
deathTriggers
Indicates that the occurrence of one entity’s death causes or initiates another event, state, or process.
-
D.
reasonForMurder
Indicates the motive or underlying cause that led someone to commit a murder.
-
E.
victimOfMurderPlot
Indicates that one entity is the intended target or victim in another entity’s plan or plot to commit murder.
- F. None of above. chosen
Provenance (4 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_69e2953344c48190875730c7d52112a0 |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f282020a5881909df47f766c3ee7af |
completed | April 29, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69f1c43e55688190b55fc20274ed471c |
completed | April 29, 2026, 8:41 a.m. |
| PDg | Predicate description generation | batch_69f1c9834064819082024233d9c6f98f |
completed | April 29, 2026, 9:04 a.m. |
Created at: April 17, 2026, 11:53 p.m.