Triple

T10192156
Position Surface form Disambiguated ID Type / Status
Subject Erik Møse E238062 entity
Predicate givenName P17 FINISHED
Object Erik E167663 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: Erik | Statement: [Erik Møse, givenName, Erik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Erik
Context triple: [Erik Møse, givenName, Erik]
  • A. Erik chosen
    Erik is a masculine given name of Scandinavian origin that is widely used across various European countries.
  • B. Erikli
    Erikli is a Turkish bottled water brand known for its natural spring water, marketed under the Nestlé Waters portfolio.
  • C. Erik Neander
    Erik Neander is a Major League Baseball executive known for leading the Tampa Bay Rays’ front office and overseeing the club’s baseball operations and roster construction.
  • D. Erik Asla
    Erik Asla is a Norwegian photographer known for his fashion and commercial work, as well as his former relationship with model Tyra Banks.
  • E. Mikael
    Mikael is a masculine given name commonly used in Scandinavian and Finnish cultures, equivalent to Michael.
  • 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_69ca84de1b208190bf17bb305b002605 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdedc4fb808190aae2e4b84be96f83 completed April 2, 2026, 4:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69d317ca2cf481909cf715ef9248be3c completed April 6, 2026, 2:17 a.m.
Created at: March 30, 2026, 9:13 p.m.