Triple

T2821570
Position Surface form Disambiguated ID Type / Status
Subject Sidney Lumet E54820 entity
Predicate child P120 FINISHED
Object Jenny Lumet
Jenny Lumet is an American screenwriter and actress best known for writing the film "Rachel Getting Married" and for her work on several prominent television series.
E302576 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: Jenny Lumet | Statement: [Sidney Lumet, child, Jenny Lumet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jenny Lumet
Context triple: [Sidney Lumet, child, Jenny Lumet]
  • A. Mary Forman
    Mary Forman is known primarily as the spouse of civil rights leader and activist James Forman.
  • B. Zosia Mamet
    Zosia Mamet is an American actress best known for her role as the eccentric and fast-talking Shoshanna Shapiro on the HBO series "Girls."
  • C. Liz Goldwyn
    Liz Goldwyn is an American filmmaker, author, and artist known for her work exploring fashion history, sexuality, and feminist themes.
  • D. Patricia Russo
    Patricia Russo is an American business executive best known for serving as CEO of Lucent Technologies and later Alcatel-Lucent.
  • E. Lee Russell
    Lee Russell was an American photographer known for his work documenting rural life and poverty in the United States as part of the Farm Security Administration project during the Great Depression.
  • 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: Jenny Lumet
Triple: [Sidney Lumet, child, Jenny Lumet]
Generated description
Jenny Lumet is an American screenwriter and actress best known for writing the film "Rachel Getting Married" and for her work on several prominent television series.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jenny Lumet
Target entity description: Jenny Lumet is an American screenwriter and actress best known for writing the film "Rachel Getting Married" and for her work on several prominent television series.
  • A. Mary Forman
    Mary Forman is known primarily as the spouse of civil rights leader and activist James Forman.
  • B. Zosia Mamet
    Zosia Mamet is an American actress best known for her role as the eccentric and fast-talking Shoshanna Shapiro on the HBO series "Girls."
  • C. Liz Goldwyn
    Liz Goldwyn is an American filmmaker, author, and artist known for her work exploring fashion history, sexuality, and feminist themes.
  • D. Patricia Russo
    Patricia Russo is an American business executive best known for serving as CEO of Lucent Technologies and later Alcatel-Lucent.
  • E. Lee Russell
    Lee Russell was an American photographer known for his work documenting rural life and poverty in the United States as part of the Farm Security Administration project during the Great Depression.
  • 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_69ab49e100c0819082a40cb797383243 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde704af88190a132626acc99745f completed March 7, 2026, 8:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69afe8b344ec8190948b26a5101fb183 completed March 10, 2026, 9:47 a.m.
NEDg Description generation batch_69afe9a000c4819085be1794bff0d506 completed March 10, 2026, 9:51 a.m.
NED2 Entity disambiguation (via description) batch_69b0010b0ddc8190b4bfb18448f88077 completed March 10, 2026, 11:31 a.m.
Created at: March 6, 2026, 9:59 p.m.