Triple
T24346853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MV Wilhelm Gustloff |
E613663
|
entity |
| Predicate | carriedPassengersOnFinalVoyage |
P881
|
FINISHED |
| Object | thousands of refugees |
—
|
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: thousands of refugees | Statement: [MV Wilhelm Gustloff, carriedPassengersOnFinalVoyage, thousands of refugees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: carriedPassengersOnFinalVoyage Context triple: [MV Wilhelm Gustloff, carriedPassengersOnFinalVoyage, thousands of refugees]
-
A.
numberOfPassengersOnFinalFlight
Indicates the total count of passengers present on the final flight in a given sequence or itinerary.
-
B.
honorsNumberOfPassengersAndCrew
Indicates that the subject recognizes or commemorates the specified count of passengers and crew.
-
C.
passengersAtTimeOfDestruction
Indicates that the specified passengers were present on or associated with the entity (e.g., a vehicle or vessel) at the moment it was destroyed.
-
D.
passengers
chosen
Indicates that one entity is traveling in or being transported by another entity, typically as a non-operating occupant.
-
E.
crewAndPassengersCount
Indicates the total number of people on a vehicle or vessel, combining both crew members and passengers.
- 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_69e2d7ddd29481909e7f539a6072bd71 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2932978b88190afc441a3d4805e5f |
completed | April 29, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69f287ad30048190b3ad3613486f277f |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 1:58 a.m.