Triple

T13102053
Position Surface form Disambiguated ID Type / Status
Subject Princess Zorka of Montenegro E310741 entity
Predicate givenName P17 FINISHED
Object Zorka
Zorka was a Montenegrin princess from the Petrović-Njegoš dynasty who became notable through her marriage into the Serbian royal family.
 E1019157 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: Zorka | Statement: [Princess Zorka of Montenegro, givenName, Zorka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zorka
Context triple: [Princess Zorka of Montenegro, givenName, Zorka]
  • A. Zedka
    Zedka is a fellow patient in Paulo Coelho’s novel "Veronika Decides to Die," known for her struggle with depression and her role in challenging Veronika’s understanding of madness and freedom.
  • B. Karcsi
    Karcsi is a common Hungarian diminutive form of the male given name Károly, used as an affectionate or informal nickname.
  • C. Husák
    Husák is a Slovak surname most prominently associated with Gustáv Husák, the communist politician who served as president of Czechoslovakia during the normalization era.
  • D. Bubi
    Bubi is a Bantu language spoken by the Bubi people, primarily on Bioko Island in Equatorial Guinea.
  • E. Bubi
    Bubi is the nickname of Erich Hartmann, the German World War II fighter pilot who became history’s highest-scoring flying ace.
  • 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: Zorka
Triple: [Princess Zorka of Montenegro, givenName, Zorka]
Generated description
Zorka was a Montenegrin princess from the Petrović-Njegoš dynasty who became notable through her marriage into the Serbian royal family.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zorka
Target entity description: Zorka was a Montenegrin princess from the Petrović-Njegoš dynasty who became notable through her marriage into the Serbian royal family.
  • A. Zedka
    Zedka is a fellow patient in Paulo Coelho’s novel "Veronika Decides to Die," known for her struggle with depression and her role in challenging Veronika’s understanding of madness and freedom.
  • B. Karcsi
    Karcsi is a common Hungarian diminutive form of the male given name Károly, used as an affectionate or informal nickname.
  • C. Husák
    Husák is a Slovak surname most prominently associated with Gustáv Husák, the communist politician who served as president of Czechoslovakia during the normalization era.
  • D. Bubi
    Bubi is the nickname of Erich Hartmann, the German World War II fighter pilot who became history’s highest-scoring flying ace.
  • E. Bubi
    Bubi is a Bantu language spoken by the Bubi people, primarily on Bioko Island in Equatorial Guinea.
  • 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_69d806a872d08190a329806f8ff30df4 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d981515d488190908d3cca1b84a42d completed April 10, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d61d88888190bfc631b759f14598 completed May 3, 2026, 4:59 a.m.
NEDg Description generation batch_69f6d7123cc48190985360c3ab76a6d0 completed May 3, 2026, 5:03 a.m.
NED2 Entity disambiguation (via description) batch_69f6d7bc235481909799b57e44f0aef2 completed May 3, 2026, 5:06 a.m.
Created at: April 9, 2026, 9:04 p.m.