Triple

T498302
Position Surface form Disambiguated ID Type / Status
Subject ALGOL W E10343 entity
Predicate influencedBy P9 FINISHED
Object ALGOL 60 E11138 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: ALGOL 60 | Statement: [ALGOL W, influencedBy, ALGOL 60]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ALGOL 60
Context triple: [ALGOL W, influencedBy, ALGOL 60]
  • A. ALGOL 60 chosen
    ALGOL 60 is an early high-level programming language that pioneered block structure and lexical scoping, profoundly influencing the design of many later languages.
  • B. 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.
  • C. ALGOL W
    ALGOL W is an early procedural programming language developed in the 1960s as a successor to ALGOL 60, notable for introducing features that strongly influenced the design of Pascal.
  • D. BCPL
    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.
  • E. ABC programming language
    ABC is an early high-level, interactive programming language developed at CWI that emphasized readability and simplicity, and later influenced the design of Python.
  • 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_69a2e847df8481909239ec08ccf1e376 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f1183e988190bce70932a9678134 completed Feb. 28, 2026, 1:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69a48a786db88190bd4486159a9f96bc completed March 1, 2026, 6:50 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.