Triple

T14356651
Position Surface form Disambiguated ID Type / Status
Subject Yisrael BaAliyah E355985 entity
Predicate notableMember P10 FINISHED
Object Marina Solodkin
Marina Solodkin was a Russian-born Israeli politician and Knesset member known for advocating immigrant rights and social justice.
E1099587 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: Marina Solodkin | Statement: [Yisrael BaAliyah, notableMember, Marina Solodkin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marina Solodkin
Context triple: [Yisrael BaAliyah, notableMember, Marina Solodkin]
  • A. Marina Zoueva
    Marina Zoueva is a renowned Russian-Canadian figure skating coach and choreographer known for guiding numerous Olympic and World champion ice dance and singles skaters.
  • B. Alexandra Yatsko
    Alexandra Yatsko is a film producer known for her work on the documentary "Love, Antosha."
  • C. Anastasia Bredikhina
    Anastasia Bredikhina is a voice actress known for her work in the animated feature film "The Peanuts Movie."
  • D. Marina Chapelin
    Marina Chapelin is a coastal marina in Varadero, Cuba, serving as a docking and service hub for recreational boats and yachts.
  • E. Yulia Solntseva
    Yulia Solntseva was a Soviet film director and actress renowned for her collaborations with Alexander Dovzhenko and for winning the Best Director award at the 1961 Cannes Film Festival.
  • 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: Marina Solodkin
Triple: [Yisrael BaAliyah, notableMember, Marina Solodkin]
Generated description
Marina Solodkin was a Russian-born Israeli politician and Knesset member known for advocating immigrant rights and social justice.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Marina Solodkin
Target entity description: Marina Solodkin was a Russian-born Israeli politician and Knesset member known for advocating immigrant rights and social justice.
  • A. Marina Zoueva
    Marina Zoueva is a renowned Russian-Canadian figure skating coach and choreographer known for guiding numerous Olympic and World champion ice dance and singles skaters.
  • B. Alexandra Yatsko
    Alexandra Yatsko is a film producer known for her work on the documentary "Love, Antosha."
  • C. Anastasia Bredikhina
    Anastasia Bredikhina is a voice actress known for her work in the animated feature film "The Peanuts Movie."
  • D. Marina Chapelin
    Marina Chapelin is a coastal marina in Varadero, Cuba, serving as a docking and service hub for recreational boats and yachts.
  • E. Yulia Solntseva
    Yulia Solntseva was a Soviet film director and actress renowned for her collaborations with Alexander Dovzhenko and for winning the Best Director award at the 1961 Cannes Film Festival.
  • 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_69d82790a7e08190877e2d349b2e8d8e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8f519bf881908615f4d47e0f77aa completed April 14, 2026, 7:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5bbd7cb881908b33b3aae4243f2e completed May 8, 2026, 3:42 a.m.
NEDg Description generation batch_69fd5c6494788190af55027c7c2c45b7 completed May 8, 2026, 3:45 a.m.
NED2 Entity disambiguation (via description) batch_69fd5cc9ec1c8190b761c9459ca0c52e completed May 8, 2026, 3:47 a.m.
Created at: April 10, 2026, 1:15 a.m.