Triple
T6026252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fedor Reingold |
E134188
|
entity |
| Predicate | wasTargetedAs |
P860
|
FINISHED |
| Object | alleged political opponent of the Soviet leadership |
—
|
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: alleged political opponent of the Soviet leadership | Statement: [Fedor Reingold, wasTargetedAs, alleged political opponent of the Soviet leadership]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasTargetedAs Context triple: [Fedor Reingold, wasTargetedAs, alleged political opponent of the Soviet leadership]
-
A.
wasTargetDuring
Indicates that an entity served as the target of another entity or action during a specified time period or event.
-
B.
usesTarget
Indicates that one entity employs, applies, or operates on another entity as its target or object of action.
-
C.
hasTarget
Indicates that one entity is directed toward, aimed at, or intended to affect another specific entity as its target.
-
D.
target
chosen
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
-
E.
coordinatedAttacksAlsoTargeted
Indicates that in a set of coordinated attacks, the same target was also attacked as part of those coordinated actions.
- 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_69c0087515148190a97475d412563865 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0560cdc308190b25ca8ecb42c4e4f |
completed | March 22, 2026, 8:50 p.m. |
| PD | Predicate disambiguation | batch_69c049e75b3881908be106fbcf8c68d4 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:07 p.m.