Triple

T18957462
Position Surface form Disambiguated ID Type / Status
Subject Frances Sternhagen E463817 entity
Predicate familyName P18 FINISHED
Object Sternhagen
Sternhagen is the surname of American actress Frances Sternhagen, known for her extensive work on stage, film, and television.
 E1351181 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: Sternhagen | Statement: [Frances Sternhagen, familyName, Sternhagen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sternhagen
Context triple: [Frances Sternhagen, familyName, Sternhagen]
  • A. Hollenstedt
    Hollenstedt is a municipality in Lower Saxony, Germany, located in the district of Harburg southwest of Hamburg.
  • B. Steinhagen
    Steinhagen is a municipality in North Rhine-Westphalia, Germany, known for its location near Bielefeld and its traditional grain distilleries.
  • C. Ramstedt
    Ramstedt is a Finnish surname most notably borne by linguist and diplomat Gustaf John Ramstedt, known for his pioneering work in Altaic and Mongolic studies.
  • D. Stedesdorf
    Stedesdorf is a small municipality in Lower Saxony, Germany, situated in the East Frisian region.
  • E. Wilhelmsdorf
    Wilhelmsdorf is a village-level subdivision of the town of Usingen in the Hochtaunus district of Hesse, Germany.
  • 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: Sternhagen
Triple: [Frances Sternhagen, familyName, Sternhagen]
Generated description
Sternhagen is the surname of American actress Frances Sternhagen, known for her extensive work on stage, film, and television.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sternhagen
Target entity description: Sternhagen is the surname of American actress Frances Sternhagen, known for her extensive work on stage, film, and television.
  • A. Hollenstedt
    Hollenstedt is a municipality in Lower Saxony, Germany, located in the district of Harburg southwest of Hamburg.
  • B. Steinhagen
    Steinhagen is a municipality in North Rhine-Westphalia, Germany, known for its location near Bielefeld and its traditional grain distilleries.
  • C. Ramstedt
    Ramstedt is a Finnish surname most notably borne by linguist and diplomat Gustaf John Ramstedt, known for his pioneering work in Altaic and Mongolic studies.
  • D. Stedesdorf
    Stedesdorf is a small municipality in Lower Saxony, Germany, situated in the East Frisian region.
  • E. Wilhelmsdorf
    Wilhelmsdorf is a village-level subdivision of the town of Usingen in the Hochtaunus district of Hesse, Germany.
  • 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_69d8dcffc278819086792a4ebfddfafa completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d5cee8348190b6506b10aed6c58a completed April 20, 2026, 7:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a059fd732f8819087374b0157bb693e completed May 14, 2026, 10:11 a.m.
NEDg Description generation batch_6a05a161c8e88190a6f9c9abe3314487 completed May 14, 2026, 10:18 a.m.
NED2 Entity disambiguation (via description) batch_6a05a1cb500481908608daee7537dd0c completed May 14, 2026, 10:19 a.m.
Created at: April 10, 2026, noon