Triple
T21461987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | death of Reinhard Heydrich |
E529493
|
entity |
| Predicate | transportUsedByVictim |
P94758
|
FINISHED |
| Object | open-top Mercedes-Benz car |
—
|
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: open-top Mercedes-Benz car | Statement: [death of Reinhard Heydrich, transportUsedByVictim, open-top Mercedes-Benz car]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transportUsedByVictim Context triple: [death of Reinhard Heydrich, transportUsedByVictim, open-top Mercedes-Benz car]
-
A.
transportThreat
Indicates a relationship where an entity moves or conveys a threat from one place or context to another.
-
B.
driverOfVictimVehicle
Indicates that an entity is the person who was driving the vehicle occupied or owned by the victim at the time of the relevant incident.
-
C.
hasModeOfTransportInAccident
chosen
Indicates that a specific mode of transport was involved in an accident associated with the given entity.
-
D.
transportAssumption
Indicates an assumption that something can be transported or carried from one place or context to another.
-
E.
utilityInvolved
Indicates that a utility service or provider is involved in, associated with, or plays a role in the referenced situation or relationship.
- 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_69e0c458133481908ae8b41a12c4edec |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9e9ef0c0881908554977df00604a6 |
completed | April 23, 2026, 9:44 a.m. |
| PD | Predicate disambiguation | batch_69e631df1b38819088d3604854e697b4 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:09 p.m.