Triple

T10225368
Position Surface form Disambiguated ID Type / Status
Subject Liv E243189 entity
Predicate hasNotableBearer P458 FINISHED
Object Liv Lisa Fries
Liv Lisa Fries is a German actress best known internationally for her role as Charlotte Ritter in the television series "Babylon Berlin."
E850330 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: Liv Lisa Fries | Statement: [Liv, hasNotableBearer, Liv Lisa Fries]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Liv Lisa Fries
Context triple: [Liv, hasNotableBearer, Liv Lisa Fries]
  • A. Lisa
    Lisa is a person known primarily for holding a position or role that was later taken over by Denise.
  • B. Lisa
    Lisa is the given name of Australian musician and composer Lisa Gerrard, renowned for her work as part of Dead Can Dance and for her film scores.
  • C. Lisa
    Lisa is the central protagonist of the film "Wicker Park," around whom the story’s romantic mystery and emotional tension revolve.
  • D. Lisa
    Lisa is a fictional character from the psychological horror film "The Voices," known for her involvement with the disturbed protagonist and the film’s darkly comedic, violent events.
  • E. Lisa
    Lisa is a feminine given name commonly used in English-speaking countries, often as a shortened form of Elizabeth or Melissa.
  • 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: Liv Lisa Fries
Triple: [Liv, hasNotableBearer, Liv Lisa Fries]
Generated description
Liv Lisa Fries is a German actress best known internationally for her role as Charlotte Ritter in the television series "Babylon Berlin."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Liv Lisa Fries
Target entity description: Liv Lisa Fries is a German actress best known internationally for her role as Charlotte Ritter in the television series "Babylon Berlin."
  • A. Lisa
    Lisa is a person known primarily for holding a position or role that was later taken over by Denise.
  • B. Lisa
    Lisa is the given name of Australian musician and composer Lisa Gerrard, renowned for her work as part of Dead Can Dance and for her film scores.
  • C. Lisa
    Lisa is the central protagonist of the film "Wicker Park," around whom the story’s romantic mystery and emotional tension revolve.
  • D. Lisa
    Lisa is a fictional character from the psychological horror film "The Voices," known for her involvement with the disturbed protagonist and the film’s darkly comedic, violent events.
  • E. Lisa
    "Lisa" is a notable work by control theorist and Stanford professor Stephen Boyd, likely associated with his research in optimization and control systems.
  • 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_69d381b0f97c819085c9b45799a5fb7c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d1f9cf6c81909a6b9e9b9d0a79fe completed April 7, 2026, 9:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6a84c80c88190846a096ae7c1d7e4 completed April 8, 2026, 7:11 p.m.
NEDg Description generation batch_69d6ab2481b081908f65806c31be807f completed April 8, 2026, 7:23 p.m.
NED2 Entity disambiguation (via description) batch_69d6ad9b943c8190bbaf201f43b7444b completed April 8, 2026, 7:33 p.m.
Created at: April 6, 2026, 11:17 a.m.