Triple
T14569358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hindenburg disaster |
E341868
|
entity |
| Predicate | passengersOnboard |
P29136
|
FINISHED |
| Object | 36 |
—
|
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: 36 | Statement: [Hindenburg disaster, passengersOnboard, 36]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: passengersOnboard Context triple: [Hindenburg disaster, passengersOnboard, 36]
-
A.
passengers
Indicates that one entity is traveling in or being transported by another entity, typically as a non-operating occupant.
-
B.
totalPeopleOnBoard
Indicates the total number of people currently present on a given vehicle, vessel, or similar conveyance.
-
C.
crewAndPassengersCount
Indicates the total number of people on a vehicle or vessel, combining both crew members and passengers.
-
D.
honorsNumberOfPassengersAndCrew
Indicates that the subject recognizes or commemorates the specified count of passengers and crew.
-
E.
passengerCount
chosen
Indicates the number of passengers associated with a given entity, such as a vehicle or trip.
- 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_69d822dcc6248190bed689984bceb0e2 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb3f2121481908f2385637944785d |
completed | April 14, 2026, 9:38 p.m. |
| PD | Predicate disambiguation | batch_69de5c57489c8190b57917be1dba6ae6 |
completed | April 14, 2026, 3:25 p.m. |
Created at: April 10, 2026, 1:23 a.m.