Triple

T2929682
Position Surface form Disambiguated ID Type / Status
Subject Max Adler E78930 entity
Predicate name P16 FINISHED
Object Max Adler E78930 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: Max Adler | Statement: [Max Adler, name, Max Adler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Max Adler
Context triple: [Max Adler, name, Max Adler]
  • A. Max Adler chosen
    Max Adler was an American businessman and philanthropist best known for founding Chicago’s Adler Planetarium, the first planetarium in the Western Hemisphere.
  • B. Stephen Endlicher
    Stephen Endlicher was a 19th-century Austrian botanist and linguist known for his influential work in plant taxonomy and classification.
  • C. Philip Steuer
    Philip Steuer is a film producer best known for his work on major studio projects, including the Disney drama "Saving Mr. Banks."
  • D. Philip Brenner
    Philip Brenner is a scholar and author known for his work on U.S. foreign policy and Latin American studies, often collaborating with historian James G. Blight.
  • E. Daniel Auster
    Daniel Auster was a prominent Zionist politician and lawyer who served as mayor of Jerusalem during the British Mandate period.
  • 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_69ad8b0d40b481908bc2a5fa2e73c3fb completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad98002da4819098d6448eebcafad4 completed March 8, 2026, 3:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69b086703868819083eacc3fe392fde1 completed March 10, 2026, 9 p.m.
Created at: March 8, 2026, 2:55 p.m.