Triple

T7725863
Position Surface form Disambiguated ID Type / Status
Subject Simple Pleasures E175127 entity
Predicate producer P490 FINISHED
Object Linda Goldstein
Linda Goldstein is a music producer known for her work on projects such as the album "Simple Pleasures."
E688854 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: Linda Goldstein | Statement: [Simple Pleasures, producer, Linda Goldstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Linda Goldstein
Context triple: [Simple Pleasures, producer, Linda Goldstein]
  • A. Suzanne Goldberg
    Suzanne Goldberg is a prominent civil rights lawyer and legal scholar known for her work on free speech and equality issues in the United States.
  • B. Suzanne Goldberg
    Suzanne Goldberg is known as the wife of prominent 1960s Free Speech Movement leader Mario Savio.
  • C. Liz Gorinsky
    Liz Gorinsky is an acclaimed science fiction and fantasy editor known for her influential work at Tor Books and for winning major genre awards.
  • D. Tina Goldstein
    Tina Goldstein is a determined American Auror in the Wizarding World franchise, prominently featured as a key ally of Newt Scamander in the Fantastic Beasts film series.
  • E. Nancy Goodman
    Nancy Goodman is an American diplomat, businesswoman, and philanthropist best known for founding the Susan G. Komen Breast Cancer Foundation.
  • 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: Linda Goldstein
Triple: [Simple Pleasures, producer, Linda Goldstein]
Generated description
Linda Goldstein is a music producer known for her work on projects such as the album "Simple Pleasures."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Linda Goldstein
Target entity description: Linda Goldstein is a music producer known for her work on projects such as the album "Simple Pleasures."
  • A. Suzanne Goldberg
    Suzanne Goldberg is a prominent civil rights lawyer and legal scholar known for her work on free speech and equality issues in the United States.
  • B. Suzanne Goldberg
    Suzanne Goldberg is known as the wife of prominent 1960s Free Speech Movement leader Mario Savio.
  • C. Liz Gorinsky
    Liz Gorinsky is an acclaimed science fiction and fantasy editor known for her influential work at Tor Books and for winning major genre awards.
  • D. Tina Goldstein
    Tina Goldstein is a determined American Auror in the Wizarding World franchise, prominently featured as a key ally of Newt Scamander in the Fantastic Beasts film series.
  • E. Nancy Goodman
    Nancy Goodman is an American diplomat, businesswoman, and philanthropist best known for founding the Susan G. Komen Breast Cancer Foundation.
  • 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_69c6995d541c81909eaa646b1a8369a9 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7031394e48190833b906af9166fe5 completed March 27, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8e581d4e881908c88d55364a5e014 completed March 29, 2026, 8:40 a.m.
NEDg Description generation batch_69c8e6f678a08190996239b643c0ffa3 completed March 29, 2026, 8:46 a.m.
NED2 Entity disambiguation (via description) batch_69c8e74688288190bbe769fe266fa37a completed March 29, 2026, 8:48 a.m.
Created at: March 27, 2026, 4:05 p.m.