Triple

T11472202
Position Surface form Disambiguated ID Type / Status
Subject Steve Jobs E271935 entity
Predicate biologicalMother P1909 FINISHED
Object Joanne Schieble E52595 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: Joanne Schieble | Statement: [Steve Jobs, biologicalMother, Joanne Schieble]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joanne Schieble
Context triple: [Steve Jobs, biologicalMother, Joanne Schieble]
  • A. Joanne Schieble chosen
    Joanne Schieble is an American woman best known as the biological mother of Apple co-founder Steve Jobs.
  • B. Anne Schaefer
    Anne Schaefer was an American silent film actress active in the early 20th century, appearing in numerous productions during the 1910s and 1920s.
  • C. Cathy Kuhlmeier
    Cathy Kuhlmeier is a former high school student who became known for challenging school censorship of a student newspaper in the landmark U.S. Supreme Court case Hazelwood School District v. Kuhlmeier.
  • D. Christine Kuehbeck
    Christine Kuehbeck is a former model best known as the wife of American investigative journalist and author Carl Bernstein.
  • E. Cynthia Scheider
    Cynthia Scheider is an American film editor known for her work on movies such as "The Taking of Pelham One Two Three" and "Kramer vs. Kramer."
  • 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_69d6aae0c8d881908a5a360c0be3242e completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8294b3f388190a587c358313f7260 completed April 9, 2026, 10:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d5e2b0408190866bbe9a3a56928b completed May 3, 2026, 4:58 a.m.
Created at: April 8, 2026, 9:35 p.m.