Triple
T4771845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sinking of HMS Prince of Wales |
E105944
|
entity |
| Predicate | airCover |
P58696
|
FINISHED |
| Object | none |
—
|
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: none | Statement: [Sinking of HMS Prince of Wales, airCover, none]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airCover Context triple: [Sinking of HMS Prince of Wales, airCover, none]
-
A.
mayCover
Indicates that one entity is permitted or able to extend over, include, or provide coverage for another entity, either partially or fully.
-
B.
typicallyCovers
Indicates that one entity is the kind of thing that usually or normally includes, addresses, or encompasses another entity.
-
C.
guaranteeCoverage
Indicates that one party commits to providing financial or protective coverage for another party or specified situation.
-
D.
bedCover
Indicates that one object functions as a covering placed over a bed.
-
E.
typeOfCoverage
Indicates the specific kind or category of coverage that applies in a given context (such as insurance, service, or protection).
- 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_69bd43f226fc8190b867cc249c2a9042 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd655e5dcc8190a932be9b1baaffb2 |
completed | March 20, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69bd6229d8448190a271719e5e30fd82 |
completed | March 20, 2026, 3:05 p.m. |
| PDg | Predicate description generation | batch_69bd6508e218819086a36236cfa4a249 |
completed | March 20, 2026, 3:17 p.m. |
Created at: March 20, 2026, 1:21 p.m.