Triple

T1117717
Position Surface form Disambiguated ID Type / Status
Subject ALGOL 60 E11138 entity
Predicate influenced P9 FINISHED
Object BCPL E51010 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: BCPL | Statement: [ALGOL 60, influenced, BCPL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BCPL
Context triple: [ALGOL 60, influenced, BCPL]
  • A. BCPL chosen
    BCPL (Basic Combined Programming Language) is an early, typeless systems programming language developed in the 1960s that significantly influenced the design of the C programming language.
  • B. Algol 68C
    Algol 68C is a compiler implementation of the Algol 68 programming language, designed to translate its advanced structured constructs into executable machine code.
  • C. Algol 68
    Algol 68 is a high-level, structured programming language from the ALGOL family, notable for its orthogonal design and influence on many later languages.
  • D. Algol 68S
    Algol 68S is a simplified subset of the Algol 68 programming language designed to make the language easier to implement and use.
  • E. Algol 68 Genie
    Algol 68 Genie is a modern, open-source implementation of the Algol 68 programming language designed for contemporary systems and practical use.
  • 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_69a493252a648190ac48f8742474a5e8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4bba425a8819099116e479552332e completed March 1, 2026, 10:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac53999b3c8190aff1cf84a3c16909 completed March 7, 2026, 4:34 p.m.
Created at: March 1, 2026, 7:43 p.m.