Triple
T14425968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German U-boat U-47 |
E357698
|
entity |
| Predicate | tonnageSunkHMSRoyalOak |
P92604
|
FINISHED |
| Object | about 29,150 tons |
—
|
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: about 29,150 tons | Statement: [German U-boat U-47, tonnageSunkHMSRoyalOak, about 29,150 tons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tonnageSunkHMSRoyalOak Context triple: [German U-boat U-47, tonnageSunkHMSRoyalOak, about 29,150 tons]
-
A.
tonnageSunk
chosen
Indicates the amount of a vessel’s weight or cargo capacity that has been destroyed or sunk, typically measured in tons.
-
B.
HMSHoodCasualtiesApproximate
Indicates that the number of casualties associated with HMS Hood is an approximate or estimated value rather than an exact count.
-
C.
firstShaftsSunk
Indicates that the initial mine shafts for a project or site have been excavated and established.
-
D.
battleshipsDamaged
Indicates that one or more battleships have sustained damage, typically as a result of combat or hostile action.
-
E.
sankOnMaidenVoyage
Indicates that the subject vessel sank during its very first voyage.
- 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_69d8279402a88190821ffa39ae15bccf |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de911398f08190be85bc0a8bef6b1b |
completed | April 14, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_69de5c30467881908e770e3940295641 |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:18 a.m.