Triple

T1229699
Position Surface form Disambiguated ID Type / Status
Subject Edvard Moser E26407 entity
Predicate hasAcademicAdvisor P167 FINISHED
Object Per Andersen E140431 NE 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: Per Andersen | Statement: [Edvard Moser, hasAcademicAdvisor, Per Andersen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Per Andersen
Context triple: [Edvard Moser, hasAcademicAdvisor, Per Andersen]
  • A. Per Andersen chosen
    Per Andersen is a Norwegian neuroscientist renowned for his pioneering work on hippocampal circuitry and synaptic plasticity.
  • B. Henrik Christensen
    Henrik Christensen is a prominent robotics researcher and academic known for his influential contributions to computer vision, autonomous systems, and robotics education.
  • C. Niels Torp
    Niels Torp is a Norwegian architect known for designing prominent public and commercial buildings in Norway and abroad.
  • D. Kristian Eidnes Andersen
    Kristian Eidnes Andersen is a Danish film composer and sound designer known for his atmospheric scores and collaborations with prominent European directors.
  • E. Rigmor Aasrud
    Rigmor Aasrud is a Norwegian Labour Party politician who has held prominent leadership roles in the national parliament and government.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69a4948571c88190a9191e451e6035fd completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be3dac2c8190914ff27173bb6b34 completed March 1, 2026, 10:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac8f7391408190928cab62e34aa361 completed March 7, 2026, 8:49 p.m.
Created at: March 1, 2026, 7:47 p.m.