Triple

T2008873
Position Surface form Disambiguated ID Type / Status
Subject Out of Africa E43646 entity
Predicate basedOnAuthor P2806 FINISHED
Object Karen Blixen
Karen Blixen, also known by her pen name Isak Dinesen, was a Danish author renowned for her memoirs and stories set in colonial Kenya, most famously "Out of Africa."
E226081 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: Karen Blixen | Statement: [Out of Africa, basedOnAuthor, Karen Blixen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karen Blixen
Context triple: [Out of Africa, basedOnAuthor, Karen Blixen]
  • A. Birgitta Dahl
    Birgitta Dahl is a Swedish Social Democratic politician who served as Speaker of the Riksdag and was a prominent figure in Sweden’s late 20th-century political landscape.
  • B. Sigrid Undset
    Sigrid Undset was a Norwegian novelist and Nobel Prize in Literature laureate best known for her medieval trilogy "Kristin Lavransdatter."
  • C. Frances Kuper
    Frances Kuper is known as a former spouse of investigative journalist and author Bob Woodward.
  • D. Astrid Lindley
    Astrid Lindley is known as the wife of late Pro Football Hall of Famer and broadcaster Frank Gifford.
  • E. Elisabeth Mann Borgese
    Elisabeth Mann Borgese was a German-born writer and pioneering advocate for international ocean governance and the law of the sea.
  • 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: Karen Blixen
Triple: [Out of Africa, basedOnAuthor, Karen Blixen]
Generated description
Karen Blixen, also known by her pen name Isak Dinesen, was a Danish author renowned for her memoirs and stories set in colonial Kenya, most famously "Out of Africa."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Karen Blixen
Target entity description: Karen Blixen, also known by her pen name Isak Dinesen, was a Danish author renowned for her memoirs and stories set in colonial Kenya, most famously "Out of Africa."
  • A. Birgitta Dahl
    Birgitta Dahl is a Swedish Social Democratic politician who served as Speaker of the Riksdag and was a prominent figure in Sweden’s late 20th-century political landscape.
  • B. Sigrid Undset
    Sigrid Undset was a Norwegian novelist and Nobel Prize in Literature laureate best known for her medieval trilogy "Kristin Lavransdatter."
  • C. Frances Kuper
    Frances Kuper is known as a former spouse of investigative journalist and author Bob Woodward.
  • D. Astrid Lindley
    Astrid Lindley is known as the wife of late Pro Football Hall of Famer and broadcaster Frank Gifford.
  • E. Elisabeth Mann Borgese
    Elisabeth Mann Borgese was a German-born writer and pioneering advocate for international ocean governance and the law of the sea.
  • 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_69a88716e9f08190946313fdc949e3cf completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb89be08c81909eb5ea672ea46b2b completed March 7, 2026, 5:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae0ae395a08190abf2077ad7a975ba completed March 8, 2026, 11:48 p.m.
NEDg Description generation batch_69ae0bb8b34c81908f817bb1fbcb1873 completed March 8, 2026, 11:52 p.m.
NED2 Entity disambiguation (via description) batch_69ae0c20aaf48190852334f9c76d0d18 completed March 8, 2026, 11:54 p.m.
Created at: March 4, 2026, 7:37 p.m.