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.