Triple

T16753501
Position Surface form Disambiguated ID Type / Status
Subject Lena Nyman E407147 entity
Predicate givenName P17 FINISHED
Object Anna Lena Elisabet Nyman E407147 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: Anna Lena Elisabet Nyman | Statement: [Lena Nyman, givenName, Anna Lena Elisabet Nyman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anna Lena Elisabet Nyman
Context triple: [Lena Nyman, givenName, Anna Lena Elisabet Nyman]
  • A. Lena Nyman chosen
    Lena Nyman was a Swedish actress known for her emotionally intense and nuanced performances in both film and theater, particularly in influential Scandinavian cinema of the 1960s and 1970s.
  • B. Lena Nilsson
    Lena Nilsson is a Swedish actress known for her work in film, television, and theater.
  • C. Maria Nilsson
    Maria Nilsson is an archaeologist known for directing research and excavations at the ancient Egyptian site of Gebel el-Silsila.
  • D. Hanna Alström
    Hanna Alström is a Swedish actress best known internationally for her role as Princess Tilde in the action-comedy film "Kingsman: The Secret Service" and its sequel.
  • E. Nilla Svensdotter
    Nilla Svensdotter was the mother of American ventriloquist and actor Edgar Bergen.
  • 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_69d8839174188190909f190097207065 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3aa28fd3c8190972e2e69ea7dece0 completed April 18, 2026, 3:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00aaf588bc8190adcc512eaa8d91e8 completed May 10, 2026, 3:57 p.m.
Created at: April 10, 2026, 5:21 a.m.