Triple
T25265330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | sinking of Patria |
E633413
|
entity |
| Predicate | numberOfPassengersOnBoardEstimate |
P882
|
FINISHED |
| Object | about 1800 |
—
|
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: about 1800 | Statement: [sinking of Patria, numberOfPassengersOnBoardEstimate, about 1800]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPassengersOnBoardEstimate Context triple: [sinking of Patria, numberOfPassengersOnBoardEstimate, about 1800]
-
A.
passengersCountApproximate
chosen
Indicates that the number of passengers involved is given as an approximate or estimated count rather than an exact figure.
-
B.
totalPeopleOnBoard
Indicates the total number of people currently present on a given vehicle, vessel, or similar conveyance.
-
C.
passengerCount
Indicates the number of passengers associated with a given entity, such as a vehicle or trip.
-
D.
crewAndPassengersCount
Indicates the total number of people on a vehicle or vessel, combining both crew members and passengers.
-
E.
passengers
Indicates that one entity is traveling in or being transported by another entity, typically as a non-operating occupant.
- 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_69e75a922ad481908f4f1f884583cb42 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f71996e1a48190ac59a1d66d7c44e8 |
completed | May 3, 2026, 9:47 a.m. |
| PD | Predicate disambiguation | batch_69f71820c6c88190ab38b4fa626d22cc |
completed | May 3, 2026, 9:40 a.m. |
Created at: April 21, 2026, 1:14 p.m.