Triple
T12914108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vergeltungswaffe 2 |
E308931
|
entity |
| Predicate | civilianCasualtiesCaused |
P34802
|
FINISHED |
| Object | several thousand |
—
|
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: several thousand | Statement: [Vergeltungswaffe 2, civilianCasualtiesCaused, several thousand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: civilianCasualtiesCaused Context triple: [Vergeltungswaffe 2, civilianCasualtiesCaused, several thousand]
-
A.
casualtiesCiviliansKilled
chosen
Indicates that the relationship records the number of civilian deaths resulting from a specific event or action.
-
B.
primaryCasualtiesFrom
Indicates that an entity is the main source or cause of the casualties experienced by another entity.
-
C.
nativeCasualties
Indicates that native or indigenous people suffered deaths or injuries as a result of a particular event, action, or conflict.
-
D.
civilianImpact
Indicates the extent to which an action, event, or situation affects civilians, especially in terms of harm, disruption, or other consequences.
-
E.
casualties
Indicates that an event, action, or situation resulted in people being killed or injured.
- 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_69d7bdf92b588190acdf2a2291ac4590 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971a0d6508190bca9668e9e06abfe |
completed | April 10, 2026, 9:54 p.m. |
| PD | Predicate disambiguation | batch_69d96fa9b7708190a9e9fa30f59ff580 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:41 p.m.