Triple

T7976790
Position Surface form Disambiguated ID Type / Status
Subject Computer Organization and Design E185466 entity
Predicate publisher P29 FINISHED
Object Morgan Kaufmann E697138 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: Morgan Kaufmann | Statement: [Computer Organization and Design, publisher, Morgan Kaufmann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Morgan Kaufmann
Context triple: [Computer Organization and Design, publisher, Morgan Kaufmann]
  • A. Morgan Kaufmann chosen
    Morgan Kaufmann is a prominent academic and professional publishing imprint known for influential books in computer science and engineering.
  • B. Addison-Wesley
    Addison-Wesley is a prominent American publishing company known for its influential textbooks and professional books in science, engineering, and computer science.
  • C. Jossey-Bass
    Jossey-Bass is an American publishing imprint known for its books on business, leadership, education, and nonprofit management.
  • D. Academic Press
    Academic Press is a prominent academic publishing company known for producing scholarly books and journals across the sciences, mathematics, and related fields.
  • E. Wiley
    Wiley is a masculine given name, often associated with notable American figures such as aviator Wiley Post.
  • 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_69ca829851908190b4e03829353ee7c3 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3bf716508190b4245bd5d89ae8c4 completed March 31, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe0cc09a081909cb92cd4864ef50d completed March 31, 2026, 2:57 p.m.
Created at: March 30, 2026, 5:14 p.m.