Triple
T37224901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blitz Wolf |
E922979
|
entity |
| Predicate | aimedAtInfluencing |
P69992
|
FINISHED |
| Object | public opinion against Nazi Germany |
—
|
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: public opinion against Nazi Germany | Statement: [Blitz Wolf, aimedAtInfluencing, public opinion against Nazi Germany]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aimedAtInfluencing Context triple: [Blitz Wolf, aimedAtInfluencing, public opinion against Nazi Germany]
-
A.
seeksToInfluence
Indicates an entity’s intention or effort to affect, shape, or alter another entity’s behavior, decisions, or state.
-
B.
aimedAtBy
chosen
Indicates that one entity serves as the target or goal toward which another entity directs an action, intention, or focus.
-
C.
influenceOf
Indicates that one entity affects, shapes, or alters the state, behavior, or properties of another entity.
-
D.
influenced
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
-
E.
influencedIn
Indicates that one entity had an effect on or shaped another entity within a specific context, domain, or setting.
- 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_69f76ea7f0008190b31b8e30f3d05a71 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb4134225081909fd60703b8cae397 |
completed | May 6, 2026, 1:25 p.m. |
| PD | Predicate disambiguation | batch_69fb35bf767081908de8345358ca7f44 |
completed | May 6, 2026, 12:36 p.m. |
Created at: May 3, 2026, 4:15 p.m.