Triple
T2650145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | shipwreck of the Princess Amelia |
E53877
|
entity |
| Predicate | mannerOfDestruction |
P21271
|
FINISHED |
| Object | sinking at sea |
—
|
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: sinking at sea | Statement: [shipwreck of the Princess Amelia, mannerOfDestruction, sinking at sea]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mannerOfDestruction Context triple: [shipwreck of the Princess Amelia, mannerOfDestruction, sinking at sea]
-
A.
hasCauseOfDestruction
Indicates that one entity is the cause or agent responsible for the destruction or damage of another entity.
-
B.
designedToDestroy
Indicates that one entity was intentionally created or configured for the purpose of damaging, disabling, or annihilating another entity.
-
C.
purposeOfDestruction
Indicates that something is destroyed with the specific aim or intention of achieving a particular goal or outcome.
-
D.
sufferedDestructionIn
Indicates that an entity experienced damage, ruin, or devastation during or as part of a specified event or period.
-
E.
demolitionMethod
chosen
Indicates the technique or process used to carry out a demolition.
- 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_69ab495e192081909c77b622e8e7e15a |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd92f5f508190b4ca396c3f399e93 |
completed | March 7, 2026, 7:52 a.m. |
| PD | Predicate disambiguation | batch_69abd814298c8190952f05aed43f6bb8 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:53 p.m.