Triple

T13003728
Position Surface form Disambiguated ID Type / Status
Subject Mikael Blomkvist E322233 entity
Predicate givenName P17 FINISHED
Object Mikael E99056 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: Mikael | Statement: [Mikael Blomkvist, givenName, Mikael]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mikael
Context triple: [Mikael Blomkvist, givenName, Mikael]
  • A. Mikael chosen
    Mikael is a masculine given name commonly used in Scandinavian and Finnish cultures, equivalent to Michael.
  • B. Johan
    Johan is the given first name of J. Erik Jonsson, an American businessman and philanthropist who co-founded Texas Instruments and served as mayor of Dallas.
  • C. Johan
    Johan is a masculine given name of Scandinavian origin, commonly used in countries such as Norway, Sweden, and Denmark.
  • D. Johan
    Johan is the given first name of the Swedish playwright and novelist August Strindberg.
  • E. Morten
    Morten is a masculine given name commonly used in Scandinavian countries, derived from the Latin name Martinus.
  • 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_69d807657e8c8190bd9435ee2f823845 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e9a2a448190968833354280e474 completed April 10, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c107f990819093042560b1bc4473 completed May 3, 2026, 3:29 a.m.
Created at: April 9, 2026, 8:47 p.m.