Triple

T10427610
Position Surface form Disambiguated ID Type / Status
Subject ALGOL E245825 entity
Predicate influenced P9 FINISHED
Object Modula E437236 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: Modula | Statement: [ALGOL, influenced, Modula]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Modula
Context triple: [ALGOL, influenced, Modula]
  • A. Modula chosen
    Modula is a procedural programming language designed by Niklaus Wirth as a successor to Pascal, notable for its support of modular programming through explicit module constructs.
  • B. Modula-2
    Modula-2 is a systems programming language designed by Niklaus Wirth that extends Pascal with modules, concurrency features, and low-level facilities for structured, efficient software development.
  • C. Mocka Modula-2
    Mocka Modula-2 is a well-known compiler and development system for the Modula-2 programming language, used primarily in academic and research contexts.
  • D. Modula-3
    Modula-3 is a systems programming language designed as a safer, more modern successor to Modula-2, emphasizing strong typing, modularity, and support for concurrency and garbage collection.
  • E. Modulen
    Modulen is a specialized medical nutrition product line from Nestlé Health Science, commonly used in the dietary management of conditions such as Crohn’s disease.
  • 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_69d381bf3dc08190bf35a2643e4e8f22 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4ea4a7dcc81909a830e08656a1c0c completed April 7, 2026, 11:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7fc2b50b48190b1d5b29d19a240c2 completed April 9, 2026, 7:21 p.m.
Created at: April 6, 2026, 12:12 p.m.