Triple

T20137759
Position Surface form Disambiguated ID Type / Status
Subject Lennart Meri E491068 entity
Predicate givenName P17 FINISHED
Object Lennart NE NERFINISHED

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: Lennart | Statement: [Lennart Meri, givenName, Lennart]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lennart
Context triple: [Lennart Meri, givenName, Lennart]
  • A. Lennart chosen
    Lennart is a masculine given name, primarily used in Germanic and Scandinavian countries, that is a cognate of the name Leonard.
  • B. Lennart Torstenson
    Lennart Torstenson was a prominent 17th-century Swedish field marshal and military commander, noted for his key role in the Thirty Years' War and Sweden’s rise as a great power.
  • C. Lennart Duse
    Lennart Duse was a person significant enough in polar or geographic exploration or research to have Duse Bay named in his honor.
  • D. Lennart Johansson
    Lennart Johansson was a Swedish football administrator best known for serving as UEFA president from 1990 to 2007 and overseeing the creation of the UEFA Champions League.
  • E. Bertil
    Bertil is a Scandinavian male given name, historically borne by nobility such as the Duke of Halland.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da62651a0c8190a3e05e95e056a66b completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e6676879f48190a59da04393d2a8cc completed April 20, 2026, 5:50 p.m.
Created at: April 11, 2026, 11:32 p.m.