Triple
T38239946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operation Catapult |
E1013732
|
entity |
| Predicate | notableShipEscaped |
P3345
|
FINISHED |
| Object | French battleship Strasbourg |
E1258124
|
NE 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: French battleship Strasbourg | Statement: [Operation Catapult, notableShipEscaped, French battleship Strasbourg]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableShipEscaped Context triple: [Operation Catapult, notableShipEscaped, French battleship Strasbourg]
-
A.
capturedShip
Indicates that one party has taken control of another party's ship, typically by force or seizure.
-
B.
shipSankIn
Indicates that a specific ship sank (was lost or submerged) in a particular location or body of water.
-
C.
notableVictimShip
Indicates that a ship is recognized as a particularly significant or noteworthy victim in a specific incident or context.
-
D.
notableShip
chosen
Indicates that there is a notable or significant ship associated with the subject entity.
-
E.
notableShipOnRoute
Indicates that a particular ship is especially significant or prominent among those operating on a given route.
- F. None of above.
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_69f76dd72a248190a5fe18db2bd1eb15 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a41cc9393088190ada4612c1e9ffdbb |
completed | June 29, 2026, 1:38 a.m. |
| PD | Predicate disambiguation | batch_6a037a1c850c819088795a7ae59bdeb8 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:30 p.m.