Triple

T10691574
Position Surface form Disambiguated ID Type / Status
Subject Bibi Andersson E252020 entity
Predicate spouse P13 FINISHED
Object Per Ahlmark E179047 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 Ahlmark | Statement: [Bibi Andersson, spouse, Per Ahlmark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Per Ahlmark
Context triple: [Bibi Andersson, spouse, Per Ahlmark]
  • A. Per Ahlmark chosen
    Per Ahlmark was a Swedish politician, writer, and former leader of the Liberal People's Party who also served as Sweden’s Deputy Prime Minister in the 1970s.
  • B. Jörgen Persson
    Jörgen Persson is a Swedish cinematographer known for his work on numerous acclaimed films, including the 1998 adaptation of Les Misérables.
  • C. Charles Boberg
    Charles Boberg is a linguist and scholar of North American English dialects, particularly known for his work on regional variation and phonology.
  • D. Erik Sparre
    Erik Sparre was a prominent Swedish statesman and nobleman who rose to become one of the kingdom’s leading political figures in the late 16th and early 17th centuries.
  • E. Jan Uddenfeldt
    Jan Uddenfeldt is a Swedish engineer and telecommunications executive best known as a key technical leader at Ericsson and a pioneer in the development of mobile communication systems.
  • 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_69d6aa5bd7c08190a816e733b4045c23 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fd3705788190bcbdef93b4c5f574 completed April 9, 2026, 1:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69e49658b5a48190813dcf114d92be8e completed April 19, 2026, 8:46 a.m.
Created at: April 8, 2026, 9:11 p.m.