Triple

T17990993
Position Surface form Disambiguated ID Type / Status
Subject Gerda Lie Kaas E430369 entity
Predicate characterPortrayed P1507 FINISHED
Object Tinka
Tinka is a fictional character portrayed by Danish actress Gerda Lie Kaas, likely in a Scandinavian film or television production.
 E1299878 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: Tinka | Statement: [Gerda Lie Kaas, characterPortrayed, Tinka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tinka
Context triple: [Gerda Lie Kaas, characterPortrayed, Tinka]
  • A. Tinka
    Tinka is a literary work by German writer Volker Braun, known for its engagement with socialist themes and critical reflection on East German society.
  • B. Tinku
    Tinku is a traditional Andean musical style rooted in Bolivian ritual combat festivals, characterized by energetic rhythms, communal singing, and indigenous instrumentation.
  • C. Tikkana
    Tikkana was a prominent 13th-century Telugu poet and scholar best known for translating a major portion of the Mahabharata into Telugu and helping shape classical Telugu literature.
  • D. Ticha
    Ticha is a retired Portuguese basketball point guard best known for her standout WNBA career, particularly with the Sacramento Monarchs.
  • E. Tiko
    Tiko is a coastal town and port in southwestern Cameroon known for its agricultural activities and role as a transport hub.
  • 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: Tinka
Triple: [Gerda Lie Kaas, characterPortrayed, Tinka]
Generated description
Tinka is a fictional character portrayed by Danish actress Gerda Lie Kaas, likely in a Scandinavian film or television production.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tinka
Target entity description: Tinka is a fictional character portrayed by Danish actress Gerda Lie Kaas, likely in a Scandinavian film or television production.
  • A. Tinka
    Tinka is a literary work by German writer Volker Braun, known for its engagement with socialist themes and critical reflection on East German society.
  • B. Tinku
    Tinku is a traditional Andean musical style rooted in Bolivian ritual combat festivals, characterized by energetic rhythms, communal singing, and indigenous instrumentation.
  • C. Tikkana
    Tikkana was a prominent 13th-century Telugu poet and scholar best known for translating a major portion of the Mahabharata into Telugu and helping shape classical Telugu literature.
  • D. Ticha
    Ticha is a retired Portuguese basketball point guard best known for her standout WNBA career, particularly with the Sacramento Monarchs.
  • E. Tiko
    Tiko is a coastal town and port in southwestern Cameroon known for its agricultural activities and role as a transport hub.
  • 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_69d8b90364248190a37381adea932f42 completed April 10, 2026, 8:46 a.m.
NER Named-entity recognition batch_69e4b29f127c81908b0c4cb3787e002c completed April 19, 2026, 10:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0337acabd481909deced9a61d84ed3 completed May 12, 2026, 2:22 p.m.
NEDg Description generation batch_6a0338cd02808190b650f59fc16bab0d completed May 12, 2026, 2:27 p.m.
NED2 Entity disambiguation (via description) batch_6a033cb498248190a3805cd356832cd0 completed May 12, 2026, 2:44 p.m.
Created at: April 10, 2026, 10:23 a.m.