Triple

T24295687
Position Surface form Disambiguated ID Type / Status
Subject Raiffeisen banks E605950 entity
Predicate riskProfileCharacteristic P3672 FINISHED
Object focus on local credit risk 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: focus on local credit risk | Statement: [Raiffeisen banks, riskProfileCharacteristic, focus on local credit risk]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: riskProfileCharacteristic
Context triple: [Raiffeisen banks, riskProfileCharacteristic, focus on local credit risk]
  • A. riskProfile chosen
    Indicates the level and characteristics of potential risk associated with an entity, action, or situation.
  • B. riskReturnProfile
    Indicates how the level of risk associated with an entity or investment corresponds to its expected or historical return.
  • C. riskFeature
    Indicates that one entity possesses or exhibits a characteristic, condition, or attribute that increases the likelihood or severity of a negative outcome for another entity or situation.
  • D. riskType
    Indicates the category or nature of risk associated with an entity, event, or relationship.
  • E. riskAttitude
    Indicates how an entity’s preferences or behavior change in response to uncertainty, reflecting its tendency to avoid, accept, or seek risk in decisions.
  • 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_69e29549335881909cbf27adcaba1cf0 completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f2915a00f08190a93a009ada096b69 completed April 29, 2026, 11:16 p.m.
PD Predicate disambiguation batch_69f1c45c6ec081908401b69424428100 completed April 29, 2026, 8:42 a.m.
Created at: April 18, 2026, 12:09 a.m.