Triple

T4833570
Position Surface form Disambiguated ID Type / Status
Subject Alexander Toshev E108001 entity
Predicate impactFactor P13420 FINISHED
Object highly cited in object detection research 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: highly cited in object detection research | Statement: [Alexander Toshev, impactFactor, highly cited in object detection research]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: impactFactor
Context triple: [Alexander Toshev, impactFactor, highly cited in object detection research]
  • A. hasCitationImpact chosen
    Indicates that one entity (such as a publication, author, or venue) exerts measurable influence on scholarly work through citations it receives or generates.
  • B. rankingImpact
    Indicates how an entity’s position or level in a ranking is affected or influenced by another factor or action.
  • C. influencedScholar
    Indicates that one scholar has had a significant intellectual or academic impact on another scholar’s work, ideas, or development.
  • D. issn
    Indicates that an entity is associated with a specific International Standard Serial Number (ISSN), identifying it as a particular serial publication.
  • E. impactCategory
    Indicates the type or domain of effect that one entity or action has on another, classifying the nature of its impact.
  • 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_69bd43fbe444819085cb970706ef73f7 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6ff981fc819080d4466c6fe06cf3 completed March 20, 2026, 4:04 p.m.
PD Predicate disambiguation batch_69bd6c21c7f08190846049d31fdfa144 completed March 20, 2026, 3:47 p.m.
Created at: March 20, 2026, 1:25 p.m.