Triple
T36258058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Empress of Britain (1931) |
E891997
|
entity |
| Predicate | passengersEvacuated |
P8973
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [SS Empress of Britain (1931), passengersEvacuated, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: passengersEvacuated Context triple: [SS Empress of Britain (1931), passengersEvacuated, yes]
-
A.
numberOfEvacuated
chosen
Indicates the total count of individuals who have been evacuated from a location or situation.
-
B.
numberOfTroopsEvacuated
Indicates the quantity of troops that have been removed from a location or situation and transported to safety.
-
C.
evacuatedBy
Indicates that an entity is removed or cleared from a place or situation through the action or assistance of another agent or process.
-
D.
numberOfEvacuatedTonsOfCargo
Indicates the quantity of cargo, measured in tons, that has been evacuated from a location or situation.
-
E.
evacuatedDuring
Indicates that one entity was removed or relocated from a place or situation during the time period or event represented by the other entity.
- 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_69f76e4599108190811532e707d6bc2c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bcccd7988190aa5c931ff347d33c |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:09 p.m.