Triple

T16868363
Position Surface form Disambiguated ID Type / Status
Subject Linda Dano E410102 entity
Predicate familyName P18 FINISHED
Object Dano
Dano is a surname most notably associated with American actress and television host Linda Dano.
E1238066 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: Dano | Statement: [Linda Dano, familyName, Dano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dano
Context triple: [Linda Dano, familyName, Dano]
  • A. Julijan
    Julijan is a given name, commonly used in Slavic regions, that corresponds to the name Julian.
  • B. Timotej
    Timotej is a masculine given name, common in Slavic countries, that is equivalent to Timothy.
  • C. Matija
    Matija is a South Slavic given name, equivalent to the English name Matthew.
  • D. Danilo
    Danilo is a masculine given name used in various Slavic and Romance languages, generally equivalent to Daniel and meaning "God is my judge."
  • E. Danijel
    Danijel is the central male protagonist in the war drama film "In the Land of Blood and Honey," which explores a complex relationship set against the backdrop of the Bosnian War.
  • 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: Dano
Triple: [Linda Dano, familyName, Dano]
Generated description
Dano is a surname most notably associated with American actress and television host Linda Dano.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Dano
Target entity description: Dano is a surname most notably associated with American actress and television host Linda Dano.
  • A. Julijan
    Julijan is a given name, commonly used in Slavic regions, that corresponds to the name Julian.
  • B. Timotej
    Timotej is a masculine given name, common in Slavic countries, that is equivalent to Timothy.
  • C. Matija
    Matija is a South Slavic given name, equivalent to the English name Matthew.
  • D. Danilo
    Danilo is a masculine given name used in various Slavic and Romance languages, generally equivalent to Daniel and meaning "God is my judge."
  • E. Danijel
    Danijel is the central male protagonist in the war drama film "In the Land of Blood and Honey," which explores a complex relationship set against the backdrop of the Bosnian War.
  • 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_69d88395e6c88190b22730f335107c14 completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b50a82348190b3e33fd558aa3c7f completed April 18, 2026, 4:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c2aba8c481908f5ff1ddc4b255cb completed May 10, 2026, 5:38 p.m.
NEDg Description generation batch_6a00c3b4a36c8190804b8616958002fc completed May 10, 2026, 5:43 p.m.
NED2 Entity disambiguation (via description) batch_6a00c434d8f88190a71c1c4c8e475e33 completed May 10, 2026, 5:45 p.m.
Created at: April 10, 2026, 5:24 a.m.