Triple

T20311113
Position Surface form Disambiguated ID Type / Status
Subject Alexa Kenin E510244 entity
Predicate familyName P18 FINISHED
Object Kenin
Kenin is a surname most notably associated with American actress Alexa Kenin, known for her film and television roles in the late 1970s and early 1980s.
 E1424228 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: Kenin | Statement: [Alexa Kenin, familyName, Kenin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kenin
Context triple: [Alexa Kenin, familyName, Kenin]
  • A. Koreets
    Koreets was a Russian Imperial Navy gunboat that gained historical note for its role in the Russo-Japanese War, particularly during the opening naval actions near Chemulpo.
  • B. Kitaj
    Kitaj is the surname of R. B. Kitaj, an influential American-born British painter associated with the School of London.
  • C. Koléa
    Koléa is a town in northern Algeria known for its historical significance and location near the Mediterranean coast in Tipaza Province.
  • D. Coree
    The Coree were a Native American people who historically lived along the coast of what is now North Carolina.
  • E. Koreiz
    Koreiz is a resort settlement on the southern coast of Crimea, known for its seaside location and historic villas.
  • 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: Kenin
Triple: [Alexa Kenin, familyName, Kenin]
Generated description
Kenin is a surname most notably associated with American actress Alexa Kenin, known for her film and television roles in the late 1970s and early 1980s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kenin
Target entity description: Kenin is a surname most notably associated with American actress Alexa Kenin, known for her film and television roles in the late 1970s and early 1980s.
  • A. Koreets
    Koreets was a Russian Imperial Navy gunboat that gained historical note for its role in the Russo-Japanese War, particularly during the opening naval actions near Chemulpo.
  • B. Kitaj
    Kitaj is the surname of R. B. Kitaj, an influential American-born British painter associated with the School of London.
  • C. Koléa
    Koléa is a town in northern Algeria known for its historical significance and location near the Mediterranean coast in Tipaza Province.
  • D. Coree
    The Coree were a Native American people who historically lived along the coast of what is now North Carolina.
  • E. Koreiz
    Koreiz is a resort settlement on the southern coast of Crimea, known for its seaside location and historic villas.
  • 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_69e0b4c7491c8190961113c4283b10b0 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e677441f9c8190acf98dc92c77732b completed April 20, 2026, 6:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08612051088190b68a6107eb941655 completed May 16, 2026, 12:20 p.m.
NEDg Description generation batch_6a086255182881908eeaa49d34bf3ba5 completed May 16, 2026, 12:25 p.m.
NED2 Entity disambiguation (via description) batch_6a08635869148190992d75a8806f767c completed May 16, 2026, 12:30 p.m.
Created at: April 16, 2026, 11:19 a.m.