Triple
T3317220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SMS Derfflinger |
E69709
|
entity |
| Predicate | engagedEnemyShips |
P47243
|
FINISHED |
| Object | British battlecruisers |
—
|
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: British battlecruisers | Statement: [SMS Derfflinger, engagedEnemyShips, British battlecruisers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: engagedEnemyShips Context triple: [SMS Derfflinger, engagedEnemyShips, British battlecruisers]
-
A.
numberOfShipsInvolved
Indicates the total count of ships that participated or were involved in a specified event or situation.
-
B.
capturedShip
Indicates that one party has taken control of another party's ship, typically by force or seizure.
-
C.
battleshipsDamaged
Indicates that one or more battleships have sustained damage, typically as a result of combat or hostile action.
-
D.
numberOfShips
Indicates the quantity of ships associated with a given entity or situation.
-
E.
effectOnShips
Indicates the impact or influence that one entity, event, or condition has on ships.
- 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_69ad85a0bb048190a5458d2738012d61 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb11230b881908f5b554323729cc5 |
completed | March 8, 2026, 5:25 p.m. |
| PD | Predicate disambiguation | batch_69ada4282730819092aa39c5f9269df0 |
completed | March 8, 2026, 4:30 p.m. |
| PDg | Predicate description generation | batch_69ada52716ec81908e89688a81039394 |
completed | March 8, 2026, 4:34 p.m. |
Created at: March 8, 2026, 3:11 p.m.