Triple

T22446439
Position Surface form Disambiguated ID Type / Status
Subject Xavier Leroy E554873 entity
Predicate notableProject P4 FINISHED
Object OCaml native-code compiler NE NERFINISHED

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: OCaml native-code compiler | Statement: [Xavier Leroy, notableProject, OCaml native-code compiler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: OCaml native-code compiler
Context triple: [Xavier Leroy, notableProject, OCaml native-code compiler]
  • A. OCaml
    OCaml is a statically typed functional programming language from the ML family, known for its powerful type system, pattern matching, and efficient native code compilation.
  • B. ocamlopt chosen
    ocamlopt is the native-code optimizing compiler for the OCaml programming language, producing efficient machine code executables.
  • C. ocamlc
    ocamlc is the bytecode compiler for the OCaml programming language, translating OCaml source code into portable bytecode executables.
  • D. ReasonML
    ReasonML is a syntax and toolchain for the OCaml language that offers a JavaScript-friendly, type-safe alternative for building web and native applications.
  • E. Standard ML of New Jersey
    Standard ML of New Jersey is a well-known, optimizing compiler and interactive environment for the Standard ML programming language, widely used in research and teaching.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e5113208190ab58c6b595f9d1d0 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15b4803908190990280ebd258cb03 completed April 29, 2026, 1:13 a.m.
Created at: April 16, 2026, 8:47 p.m.