Triple

T2932411
Position Surface form Disambiguated ID Type / Status
Subject Thorbjørn Jagland E78983 entity
Predicate spouse P13 FINISHED
Object Hanne Grotjord
Hanne Grotjord is the wife of Norwegian politician and former Prime Minister Thorbjørn Jagland.
 E314686 NE FINISHED

How this triple was built (4 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: Hanne Grotjord | Statement: [Thorbjørn Jagland, spouse, Hanne Grotjord]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hanne Grotjord
Context triple: [Thorbjørn Jagland, spouse, Hanne Grotjord]
  • A. Bergljot Bech
    Bergljot Bech was the wife of Norwegian Nobel Prize–winning author Knut Hamsun and a figure in early 20th-century Norwegian cultural life.
  • B. Inger Skramstad
    Inger Skramstad is known as the spouse of Norwegian-American physicist and Nobel laureate Ivar Giaever.
  • C. Suzanne Brøgger
    Suzanne Brøgger is a Danish author and essayist known for her provocative, feminist, and often autobiographical explorations of sexuality, identity, and social norms.
  • D. Ingeborg Holm
    Ingeborg Holm is a character in Thomas Mann’s novella "Tonio Kröger," representing part of the bourgeois world that shapes the protagonist’s conflicted feelings about art and ordinary life.
  • E. Inge Nissen
    Inge Nissen is a former Danish basketball star best known for her standout collegiate career at Old Dominion University and subsequent induction into multiple halls of fame.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Hanne Grotjord
Triple: [Thorbjørn Jagland, spouse, Hanne Grotjord]
Generated description
Hanne Grotjord is the wife of Norwegian politician and former Prime Minister Thorbjørn Jagland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hanne Grotjord
Target entity description: Hanne Grotjord is the wife of Norwegian politician and former Prime Minister Thorbjørn Jagland.
  • A. Bergljot Bech
    Bergljot Bech was the wife of Norwegian Nobel Prize–winning author Knut Hamsun and a figure in early 20th-century Norwegian cultural life.
  • B. Inger Skramstad
    Inger Skramstad is known as the spouse of Norwegian-American physicist and Nobel laureate Ivar Giaever.
  • C. Suzanne Brøgger
    Suzanne Brøgger is a Danish author and essayist known for her provocative, feminist, and often autobiographical explorations of sexuality, identity, and social norms.
  • D. Ingeborg Holm
    Ingeborg Holm is a character in Thomas Mann’s novella "Tonio Kröger," representing part of the bourgeois world that shapes the protagonist’s conflicted feelings about art and ordinary life.
  • E. Inge Nissen
    Inge Nissen is a former Danish basketball star best known for her standout collegiate career at Old Dominion University and subsequent induction into multiple halls of fame.
  • F. None of above. chosen

Provenance (5 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_69ad8b0d40b481908bc2a5fa2e73c3fb completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad983a4ae08190aa1aeb2747abd1a1 completed March 8, 2026, 3:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b0fc6c2cc08190ab34973c3f33a34d completed March 11, 2026, 5:23 a.m.
NEDg Description generation batch_69b0fd5e0ce081909a3fe89afc57a708 completed March 11, 2026, 5:27 a.m.
NED2 Entity disambiguation (via description) batch_69b1011c30ec8190a61b447733c7d4e7 completed March 11, 2026, 5:43 a.m.
Created at: March 8, 2026, 2:55 p.m.