Triple

T12730807
Position Surface form Disambiguated ID Type / Status
Subject Lavon Hayes E304230 entity
Predicate creator P184 FINISHED
Object Leila Gerstein E240305 NE FINISHED

How this triple was built (2 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: Leila Gerstein | Statement: [Lavon Hayes, creator, Leila Gerstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leila Gerstein
Context triple: [Lavon Hayes, creator, Leila Gerstein]
  • A. Leila Gerstein chosen
    Leila Gerstein is an American television writer and producer best known for creating the comedy-drama series "Hart of Dixie."
  • B. Margot Löwenthal
    Margot Löwenthal was the daughter of Elsa Löwenthal, who was Albert Einstein’s second wife and cousin.
  • C. Miriam Mendelsohn
    Miriam Mendelsohn is a loyal, upbeat, and supportive best friend of Mei Lee in Pixar's animated film "Turning Red."
  • D. Esther Raab
    Esther Raab was a Jewish Holocaust survivor known for escaping from the Sobibor extermination camp and later bearing witness to its atrocities.
  • E. Esther Kreitman
    Esther Kreitman was a pioneering Yiddish writer and the older sister of Isaac Bashevis Singer, known for her psychologically rich portrayals of Jewish women's lives in Eastern Europe.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d7bdf1426c8190a4402e1c4cdec33a completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96467a2248190aff1ebb5db84b3c6 completed April 10, 2026, 8:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76b96f72881909090691e99bb2425 completed May 3, 2026, 3:36 p.m.
Created at: April 9, 2026, 5:25 p.m.