Triple

T342152
Position Surface form Disambiguated ID Type / Status
Subject Diamonds E6857 entity
Predicate costumeDesigner P184 FINISHED
Object Karinska
Karinska was a renowned 20th-century costume designer best known for her influential work in ballet and theater, particularly with the New York City Ballet.
 E44528 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: Karinska | Statement: [Diamonds, costumeDesigner, Karinska]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Karinska
Context triple: [Diamonds, costumeDesigner, Karinska]
  • A. Kamen
    Kamen is a surname most prominently associated with American inventor and entrepreneur Dean Kamen, known for creating the Segway and numerous medical devices.
  • B. Kutaisi
    Kutaisi is one of Georgia’s major cities, historically significant and formerly a capital, located in the western part of the country.
  • C. Kareli
    Kareli is a town in central Georgia that serves as an important local center within the Shida Kartli region.
  • D. Bór
    Bór is the wartime nickname of Tadeusz Bór-Komorowski, the Polish general who commanded the Home Army and led the Warsaw Uprising during World War II.
  • E. Skaugum
    Skaugum is the official country residence of the Norwegian royal family, located in Asker near Oslo.
  • 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: Karinska
Triple: [Diamonds, costumeDesigner, Karinska]
Generated description
Karinska was a renowned 20th-century costume designer best known for her influential work in ballet and theater, particularly with the New York City Ballet.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Karinska
Target entity description: Karinska was a renowned 20th-century costume designer best known for her influential work in ballet and theater, particularly with the New York City Ballet.
  • A. Kamen
    Kamen is a surname most prominently associated with American inventor and entrepreneur Dean Kamen, known for creating the Segway and numerous medical devices.
  • B. Kutaisi
    Kutaisi is one of Georgia’s major cities, historically significant and formerly a capital, located in the western part of the country.
  • C. Kareli
    Kareli is a town in central Georgia that serves as an important local center within the Shida Kartli region.
  • D. Bór
    Bór is the wartime nickname of Tadeusz Bór-Komorowski, the Polish general who commanded the Home Army and led the Warsaw Uprising during World War II.
  • E. Skaugum
    Skaugum is the official country residence of the Norwegian royal family, located in Asker near Oslo.
  • 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_69a2e7951ba08190960e90823b5078f3 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2eafef8c88190a5932eb2c6ac4a5d completed Feb. 28, 2026, 1:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3dd2ff66c8190a0e688e4f9baa5b4 completed March 1, 2026, 6:31 a.m.
NEDg Description generation batch_69a3ddbbe7e08190ac167e158d19dbce completed March 1, 2026, 6:33 a.m.
NED2 Entity disambiguation (via description) batch_69a3de3fef7c819082193eb7083175e1 completed March 1, 2026, 6:35 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.