Triple
T26939915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No. 304 Polish Bomber Squadron |
E678482
|
entity |
| Predicate | engagedEnemyType |
P99416
|
FINISHED |
| Object | German shipping |
—
|
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: German shipping | Statement: [No. 304 Polish Bomber Squadron, engagedEnemyType, German shipping]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: engagedEnemyType Context triple: [No. 304 Polish Bomber Squadron, engagedEnemyType, German shipping]
-
A.
enemyType
Indicates that one entity is classified as an enemy of a specified type or category in relation to another entity.
-
B.
enemyForceType
chosen
Indicates that one entity is characterized as a hostile or opposing force of a specified type relative to another entity.
-
C.
enemyCharacterIn
Indicates that a character is located within or present inside an enemy-controlled area, zone, or context.
-
D.
primaryEnemy
Indicates that one entity is the main or most significant adversary or opponent of another entity.
-
E.
hasOpposingForceType
Indicates that one force is characterized as being of a type that opposes or counteracts another force.
- 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_69eeeb4d69588190a7c912164a1c37b3 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f621cbc48881908d104c648c91c715 |
completed | May 2, 2026, 4:09 p.m. |
| PD | Predicate disambiguation | batch_69f620e0b37481909a280574decbd443 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 6:17 a.m.