Triple
T36258059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SS Empress of Britain (1931) |
E891997
|
entity |
| Predicate | largestLinerSunkByUBoat |
P185068
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [SS Empress of Britain (1931), largestLinerSunkByUBoat, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: largestLinerSunkByUBoat Context triple: [SS Empress of Britain (1931), largestLinerSunkByUBoat, true]
-
A.
sunkBy
Indicates that one entity (typically a vessel or structure) was caused to sink or be destroyed in water by another entity.
-
B.
firstShaftsSunk
Indicates that the initial mine shafts for a project or site have been excavated and established.
-
C.
mostShipsLostIn
Indicates that an entity experienced the highest number of ships lost during a specified event, period, or context compared to others.
-
D.
tonnageSunk
Indicates the amount of a vessel’s weight or cargo capacity that has been destroyed or sunk, typically measured in tons.
-
E.
wasSunkAs
Indicates that an entity met its end by being sunk in a specified role, context, or capacity.
- F. None of above. chosen
Provenance (4 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_69f7bb1d6b70819091227bd011734d19 |
completed | May 3, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a4aad48190a62e41c5e39339d9 |
completed | May 3, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69f7ba6c27e081908868a2b50d1d603c |
completed | May 3, 2026, 9:13 p.m. |
Created at: May 3, 2026, 4:09 p.m.