Triple

T805101
Position Surface form Disambiguated ID Type / Status
Subject Codex E17412 entity
Predicate supportsLanguage P2177 FINISHED
Object Scala E71988 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: Scala | Statement: [Codex, supportsLanguage, Scala]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Scala
Context triple: [Codex, supportsLanguage, Scala]
  • A. Scala chosen
    Scala is a high-level, statically typed programming language that unifies object-oriented and functional programming paradigms and runs on the Java Virtual Machine.
  • B. Kotlin
    Kotlin is a modern, statically typed programming language developed by JetBrains that runs on the JVM and is widely used for building Android applications.
  • C. F#
    F# is a functional-first, multi-paradigm programming language for the .NET platform, known for its strong type system and concise, expressive syntax.
  • D. Java
    Java is a large, densely populated island in Indonesia that has long served as the country’s political and economic center.
  • E. Java
    Java is a widely used, object-oriented programming language known for its platform independence and extensive use in enterprise, web, and mobile application development.
  • 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_69a4937ae8a08190b5084a03d532b30e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4aabff3d88190bec4299fa0d87df0 completed March 1, 2026, 9:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69a68926c04081908923a7d114d1842d completed March 3, 2026, 7:09 a.m.
Created at: March 1, 2026, 7:38 p.m.