Triple
T17658977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bruno Antony |
E440199
|
entity |
| Predicate | methodOfMurderScheme |
P128435
|
FINISHED |
| Object | exchange of murders between strangers |
—
|
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: exchange of murders between strangers | Statement: [Bruno Antony, methodOfMurderScheme, exchange of murders between strangers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: methodOfMurderScheme Context triple: [Bruno Antony, methodOfMurderScheme, exchange of murders between strangers]
-
A.
reasonForMurder
Indicates the motive or underlying cause that led someone to commit a murder.
-
B.
hasMurderer
Indicates that one entity is the person who committed the murder of another entity.
-
C.
revealsMurderTo
Indicates that one entity discloses information about a murder to another entity.
-
D.
hasPartInMurderOf
Indicates involvement as a contributing participant in the commission of a murder.
-
E.
featuresMurderInvestigation
Indicates that the subject involves or includes a murder investigation as a central element or storyline.
- 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_69d8b9e87e18819087104a44dc4dc5b1 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46ea469448190b2753571f8493aef |
completed | April 19, 2026, 5:56 a.m. |
| PD | Predicate disambiguation | batch_69e3cde007d8819090dd92eea9f022cc |
completed | April 18, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69e3cfaac2b881909e1140339eb1a0dd |
completed | April 18, 2026, 6:38 p.m. |
Created at: April 10, 2026, 9:37 a.m.