Triple
T5816271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Treaty of Küçük Kaynarca |
E128993
|
entity |
| Predicate | increasedInfluenceOf |
P63153
|
FINISHED |
| Object | Russian Empire in the Ottoman Empire |
—
|
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: Russian Empire in the Ottoman Empire | Statement: [Treaty of Küçük Kaynarca, increasedInfluenceOf, Russian Empire in the Ottoman Empire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: increasedInfluenceOf Context triple: [Treaty of Küçük Kaynarca, increasedInfluenceOf, Russian Empire in the Ottoman Empire]
-
A.
hasSignificantInfluenceIn
chosen
Indicates that one entity exerts a substantial impact or shaping effect on another entity within a particular domain, context, or outcome.
-
B.
typeOfInfluence
Indicates the specific nature or category of influence that one entity exerts on another.
-
C.
influenced
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
-
D.
seeksToInfluence
Indicates an entity’s intention or effort to affect, shape, or alter another entity’s behavior, decisions, or state.
-
E.
influencedDiscussionOf
Indicates that one entity had an effect on the way another entity was discussed, framed, or debated.
- 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_69c0084869e881908d7859492183ca7b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0400f1af881908d376ea4793f6dea |
completed | March 22, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69c0333fdd7081908d829265caa2ac11 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:53 p.m.