Triple

T5168242
Position Surface form Disambiguated ID Type / Status
Subject Iranian toman E116610 entity
Predicate confusionRisk P9984 FINISHED
Object difference between written rials and spoken tomans can cause misunderstanding 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: difference between written rials and spoken tomans can cause misunderstanding | Statement: [Iranian toman, confusionRisk, difference between written rials and spoken tomans can cause misunderstanding]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: confusionRisk
Context triple: [Iranian toman, confusionRisk, difference between written rials and spoken tomans can cause misunderstanding]
  • A. risk chosen
    Indicates that one entity is exposed or subject to potential harm, loss, or adverse outcome arising from another entity, action, or situation.
  • B. riskType
    Indicates the category or nature of risk associated with an entity, event, or relationship.
  • C. riskTaken
    Indicates that an entity has undertaken an action or decision involving exposure to potential loss, harm, or uncertainty.
  • D. uncertainty
    Indicates that there is doubt, lack of sureness, or incomplete confidence about a fact, outcome, or state of affairs in the relationship or situation described.
  • E. riskLevel
    Indicates the degree of potential harm, loss, or adverse outcome associated with a particular situation, action, or entity.
  • 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_69bd445ff97c81909a2615cc56235470 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd794b87508190be3b82726ef4b37c completed March 20, 2026, 4:43 p.m.
PD Predicate disambiguation batch_69bd77b36c008190b91011a9fa52b3d2 completed March 20, 2026, 4:37 p.m.
Created at: March 20, 2026, 1:45 p.m.