Triple

T4833564
Position Surface form Disambiguated ID Type / Status
Subject Alexander Toshev E108001 entity
Predicate worksOnProblem P2453 FINISHED
Object localizing objects in images 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: localizing objects in images | Statement: [Alexander Toshev, worksOnProblem, localizing objects in images]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: worksOnProblem
Context triple: [Alexander Toshev, worksOnProblem, localizing objects in images]
  • A. worksOnIssue chosen
    Indicates that an entity (typically a person or team) is actively engaged in addressing, resolving, or contributing work toward a specific issue.
  • B. worksAgainst
    Indicates that one entity actively opposes, counteracts, or undermines the goals, effects, or interests of another entity.
  • C. worksThrough
    Indicates that one entity performs an action, causes an effect, or achieves a result by using, employing, or acting via another entity as an intermediary or means.
  • D. worksTo
    Indicates that one entity performs work or exerts effort in order to achieve, support, or contribute to another entity or outcome.
  • E. worksFor
    Indicates that one entity is employed by or performs work on behalf of another entity, typically an organization or individual.
  • 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.