Triple

T19111831
Position Surface form Disambiguated ID Type / Status
Subject PlusCal E467808 entity
Predicate canBeTranslatedTo P103789 FINISHED
Object TLA+ NE NERFINISHED

How this triple was built (3 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: TLA+ | Statement: [PlusCal, canBeTranslatedTo, TLA+]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TLA+
Context triple: [PlusCal, canBeTranslatedTo, TLA+]
  • A. TLA+ chosen
    TLA+ is a formal specification language developed by Leslie Lamport for modeling and verifying concurrent and distributed systems using mathematical logic.
  • B. TLA+ model checker TLC
    TLA+ model checker TLC is an automated verification tool that exhaustively explores the state space of TLA+ specifications to detect errors such as deadlocks, invariant violations, and liveness issues.
  • C. PlusCal algorithm language
    PlusCal algorithm language is a high-level pseudocode-style language designed by Leslie Lamport for writing and reasoning about algorithms that can be automatically translated into TLA+ specifications.
  • D. TLC model checker
    The TLC model checker is a tool for exhaustively verifying TLA+ specifications by exploring all possible system behaviors to detect errors such as deadlocks and invariant violations.
  • E. Dafny programming language
    Dafny is a verification-aware programming language and toolchain designed to support formal specification, automated proof of correctness, and executable code generation for imperative and functional programs.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: canBeTranslatedTo
Context triple: [PlusCal, canBeTranslatedTo, TLA+]
  • A. canTranslateBetween chosen
    Indicates that an entity has the ability to translate or convert information accurately between two specified languages, formats, or representation systems.
  • B. canTranslateAlong
    Indicates that one entity is able to be moved or shifted along the path, direction, or frame of reference defined by another entity.
  • C. hasTranslation
    Indicates that one entity is a translation or translated version of another entity in a different language.
  • D. hasTranslated
    Indicates that one entity has rendered the content of another entity from one language into a different language.
  • E. usedToTranslate
    Indicates that one entity served as the tool, method, or medium for translating another entity from one language or representation to another.
  • F. None of above.

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_69d8dd06a26481908039e2a1bae8c597 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e394969c81909d09b2300ea0e041 completed April 20, 2026, 8:28 a.m.
PD Predicate disambiguation batch_69e4b9ac41848190afd0f33b42cebe99 completed April 19, 2026, 11:17 a.m.
Created at: April 10, 2026, 12:04 p.m.