Triple
T36258060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Empress of Britain (1931) |
E891997
|
entity |
| Predicate | sunkByNavy |
P4687
|
FINISHED |
| Object | Kriegsmarine U-boat arm |
—
|
NE NERFINISHED |
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: Kriegsmarine U-boat arm | Statement: [SS Empress of Britain (1931), sunkByNavy, Kriegsmarine U-boat arm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sunkByNavy Context triple: [SS Empress of Britain (1931), sunkByNavy, Kriegsmarine U-boat arm]
-
A.
sunkBy
chosen
Indicates that one entity (typically a vessel or structure) was caused to sink or be destroyed in water by another entity.
-
B.
sunkDuring
Indicates that one entity was sunk in the course of, or as a result of, the event or time period represented by another entity.
-
C.
shipSankIn
Indicates that a specific ship sank (was lost or submerged) in a particular location or body of water.
-
D.
sankOnMaidenVoyage
Indicates that the subject vessel sank during its very first voyage.
-
E.
wasSunkAs
Indicates that an entity met its end by being sunk in a specified role, context, or capacity.
- 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_69f7b5fece288190bd538ba5391d45e7 |
completed | May 3, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c44390819084fb5558b354658f |
completed | May 3, 2026, 8:49 p.m. |
Created at: May 3, 2026, 4:09 p.m.