Triple

T16635351
Position Surface form Disambiguated ID Type / Status
Subject Eat a Bowl of Tea E404183 entity
Predicate musicBy P1952 FINISHED
Object Mark Adler E818637 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: Mark Adler | Statement: [Eat a Bowl of Tea, musicBy, Mark Adler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mark Adler
Context triple: [Eat a Bowl of Tea, musicBy, Mark Adler]
  • A. Mark Adler chosen
    Mark Adler is an American film composer known for scoring documentaries and feature films, including the acclaimed documentary "Food, Inc."
  • B. Phil Zimmermann
    Phil Zimmermann is an American cryptographer best known as the creator of Pretty Good Privacy (PGP), a widely used email encryption software that helped popularize strong cryptography for the public.
  • C. Bruce Perens
    Bruce Perens is a prominent open-source advocate and co-founder of the Open Source Initiative, known for authoring the Debian Free Software Guidelines and the Open Source Definition.
  • D. Oren Patashnik
    Oren Patashnik is a computer scientist best known for coauthoring the influential textbook "Concrete Mathematics" and for creating the BibTeX reference management tool used with LaTeX.
  • E. L. Peter Deutsch
    L. Peter Deutsch is a computer scientist and software developer best known for creating the Ghostscript interpreter for the PostScript language and PDF files.
  • 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_69d8838a41f08190b0c3f79c47df5078 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e378e999d48190bff680040dbc883d completed April 18, 2026, 12:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a007dc05bd881909c6b2e0d95622aa1 completed May 10, 2026, 12:44 p.m.
Created at: April 10, 2026, 5:17 a.m.