Triple
T33088728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Convoy PQ 17 |
E846712
|
entity |
| Predicate | lostShips |
P821
|
FINISHED |
| Object | 24 merchant ships sunk |
—
|
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: 24 merchant ships sunk | Statement: [Convoy PQ 17, lostShips, 24 merchant ships sunk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lostShips Context triple: [Convoy PQ 17, lostShips, 24 merchant ships sunk]
-
A.
shipsSunkOrTotalLoss
chosen
Indicates that the referenced ships were sunk or otherwise rendered a total loss (permanently unusable).
-
B.
shipSankIn
Indicates that a specific ship sank (was lost or submerged) in a particular location or body of water.
-
C.
shipwrecksDestroyedIn
Indicates that one or more shipwrecks were destroyed within a specified location or during a particular event or time period.
-
D.
mostShipsLostIn
Indicates that an entity experienced the highest number of ships lost during a specified event, period, or context compared to others.
-
E.
shipTypeSunk
Indicates that a particular type of ship has been sunk as a result of some event or action.
- 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_69f3495590dc8190aa04f3dec74ce976 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d6a6b04c8190bee4cf9c00665ef7 |
completed | May 3, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69f6d27120988190aacec621cf2bf0e8 |
completed | May 3, 2026, 4:43 a.m. |
Created at: May 1, 2026, 1:26 a.m.