Triple
T36372859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Empress of Canada (1971) |
E895810
|
entity |
| Predicate | passengerCapacityAsCruiseShip |
P11680
|
FINISHED |
| Object | about 1200 |
—
|
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 1200 | Statement: [SS Empress of Canada (1971), passengerCapacityAsCruiseShip, about 1200]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: passengerCapacityAsCruiseShip Context triple: [SS Empress of Canada (1971), passengerCapacityAsCruiseShip, about 1200]
-
A.
typicalPassengerCapacityPerShip
Indicates the usual number of passengers that a ship of a given type or class is designed or expected to carry.
-
B.
capacityPerCabin
Indicates the number of occupants or units that each individual cabin is designed or allowed to hold.
-
C.
cruiseCapability
Indicates the ability of an entity to travel or operate in a steady, sustained cruising mode under its own power.
-
D.
maximumPassengerCapacity
chosen
Indicates the greatest number of passengers that an entity is designed or allowed to carry at one time.
-
E.
additionalEmbarkedPersonnelCapacity
Indicates the maximum number of extra personnel that can be taken on board beyond the standard embarked complement.
- 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_69f76e5115588190ad8738860b7bc68b |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c475c58c8190a883554231e88c88 |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:10 p.m.