Triple

T20518154
Position Surface form Disambiguated ID Type / Status
Subject Bibi Besch E503733 entity
Predicate givenName P17 FINISHED
Object Bibiana
Bibiana is a feminine given name of Latin origin, often associated with the actress Bibi Besch whose full first name it is.
 E1436049 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: Bibiana | Statement: [Bibi Besch, givenName, Bibiana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bibiana
Context triple: [Bibi Besch, givenName, Bibiana]
  • A. Djanira
    Djanira was a prominent Brazilian modernist painter known for her vivid depictions of everyday life, religious themes, and popular culture.
  • B. Martita
    Martita is a Spanish affectionate diminutive form of the given name Marta, often used to express endearment or familiarity.
  • C. Jolanda
    Jolanda is a feminine given name, commonly considered a variant of Yolanda, used in various European countries.
  • D. Corina
    Corina is a feminine given name used in various cultures, often considered a variant of names like Corine or Corinna.
  • E. Rosana
    Rosana is a municipality in the state of São Paulo, Brazil, known for hosting a campus of São Paulo State University (UNESP).
  • 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: Bibiana
Triple: [Bibi Besch, givenName, Bibiana]
Generated description
Bibiana is a feminine given name of Latin origin, often associated with the actress Bibi Besch whose full first name it is.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bibiana
Target entity description: Bibiana is a feminine given name of Latin origin, often associated with the actress Bibi Besch whose full first name it is.
  • A. Djanira
    Djanira was a prominent Brazilian modernist painter known for her vivid depictions of everyday life, religious themes, and popular culture.
  • B. Martita
    Martita is a Spanish affectionate diminutive form of the given name Marta, often used to express endearment or familiarity.
  • C. Jolanda
    Jolanda is a feminine given name, commonly considered a variant of Yolanda, used in various European countries.
  • D. Corina
    Corina is a feminine given name used in various cultures, often considered a variant of names like Corine or Corinna.
  • E. Rosana
    Rosana is a municipality in the state of São Paulo, Brazil, known for hosting a campus of São Paulo State University (UNESP).
  • 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_69e0b4b2aa788190ae9eb37c1d73b1f1 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e69f43e0b08190b043f35645b264a0 completed April 20, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a089d3d55a08190b478b4b8f50ff101 completed May 16, 2026, 4:37 p.m.
NEDg Description generation batch_6a089e5816308190979cd7ab78a0c0f6 completed May 16, 2026, 4:42 p.m.
NED2 Entity disambiguation (via description) batch_6a089ecd0f988190afc859a511a18f7b completed May 16, 2026, 4:43 p.m.
Created at: April 16, 2026, 11:36 a.m.