Triple
T32732303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Bastard |
E836985
|
entity |
| Predicate | hasPassengerAtFatalCrash |
P115240
|
FINISHED |
| Object | Rolf Wütherich |
—
|
NE NERFINISHED |
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: Rolf Wütherich | Statement: [Little Bastard, hasPassengerAtFatalCrash, Rolf Wütherich]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPassengerAtFatalCrash Context triple: [Little Bastard, hasPassengerAtFatalCrash, Rolf Wütherich]
-
A.
coPassengerInFatalCrashWith
chosen
Indicates that two or more individuals were passengers in the same vehicle involved in a fatal crash.
-
B.
hasModeOfTransportInAccident
Indicates that a specific mode of transport was involved in an accident associated with the given entity.
-
C.
fatalitiesOnboard
Indicates that the relationship specifies the number of people who died among those present on a particular vehicle or craft.
-
D.
pilotAtFatalCrash
Indicates that the specified person was serving as the pilot at the time and location of a fatal crash.
-
E.
hasThroughPassengersWith
Indicates that two transportation segments, services, or locations are connected by passengers who travel through them without starting or ending their journey there.
- 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_69f34935fb048190ad4967420581f835 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69ff17be6ad48190963206f2619b1b28 |
completed | May 9, 2026, 11:17 a.m. |
| PD | Predicate disambiguation | batch_69ff1724ba24819092c928fcbcb286ec |
completed | May 9, 2026, 11:14 a.m. |
Created at: May 1, 2026, 1:11 a.m.