Triple

T38415161
Position Surface form Disambiguated ID Type / Status
Subject Alexander Gustafsson E901581 entity
Predicate reachSpecialty P466 FINISHED
Object effective use of reach and boxing 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: effective use of reach and boxing | Statement: [Alexander Gustafsson, reachSpecialty, effective use of reach and boxing]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: reachSpecialty
Context triple: [Alexander Gustafsson, reachSpecialty, effective use of reach and boxing]
  • A. hasSpecialty chosen
    Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
  • B. isConsideredSpecialtyOf
    Indicates that one field, practice, or area of expertise is regarded as a specialized branch or subset of another broader field.
  • C. subjectSpecialization
    Indicates that one subject focuses on, or has expertise in, a particular field, topic, or area of knowledge.
  • D. hasSpecialist
    Indicates that one entity is associated with or assigned to a specialist entity that provides expert support, service, or oversight for it.
  • E. openingSpecialty
    Indicates the specific area of focus, expertise, or type associated with an opening (such as a job, position, or opportunity).
  • 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_69f76e61e79c81908b787d83b46ab92b completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69fcd1499e2c81909bafd84dc4810f45 completed May 7, 2026, 5:52 p.m.
PD Predicate disambiguation batch_69fcccf024ec819086383ffbb6cfc036 completed May 7, 2026, 5:33 p.m.
Created at: May 3, 2026, 4:31 p.m.