Triple
T481922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German attack on Westerplatte |
E9186
|
entity |
| Predicate | hasForcesInvolved |
P14890
|
FINISHED |
| Object | German Army units |
—
|
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 Army units | Statement: [German attack on Westerplatte, hasForcesInvolved, German Army units]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasForcesInvolved Context triple: [German attack on Westerplatte, hasForcesInvolved, German Army units]
-
A.
involvesWeaponType
Indicates that the relationship or action includes the use, presence, or association of a specific type or category of weapon.
-
B.
involvesProjectile
Indicates that the action or event includes the use, presence, or motion of a projectile as a key component of the interaction between entities.
-
C.
involvedPhysicalEffect
Indicates that one entity participates in causing, experiencing, or mediating a physical effect on another entity or the environment.
-
D.
attackedIn
Indicates that one entity carried out an attack in the location, context, or time frame specified by another entity or value.
-
E.
numberOfTroopsInvolved
Indicates the quantity of military personnel participating in or assigned to a specific operation, event, or engagement.
- 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_69a2e7ff81708190b0507a24a997232c |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f05a7f6c819082b4a5a3e69468a6 |
completed | Feb. 28, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69a2edf321288190b5d560f75782c2cb |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2ef4030608190b39852b347a505ca |
completed | Feb. 28, 2026, 1:36 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.