Triple

T575074
Position Surface form Disambiguated ID Type / Status
Subject Java E13745 entity
Predicate influenced P9 FINISHED
Object Scala
Scala is a high-level, statically typed programming language that unifies object-oriented and functional programming paradigms and runs on the Java Virtual Machine.
 E71988 NE FINISHED

How this triple was built (4 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: [Java, influenced, Scala]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Scala
Context triple: [Java, influenced, Scala]
  • A. 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.
  • B. F#
    F# is a functional-first, multi-paradigm programming language for the .NET platform, known for its strong type system and concise, expressive syntax.
  • C. Java
    Java is a large, densely populated island in Indonesia that has long served as the country’s political and economic center.
  • D. 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.
  • E. Julia
    Julia is a high-level, high-performance programming language designed for numerical computing, data science, and scientific research, combining the ease of dynamic languages with the speed of compiled languages.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Scala
Triple: [Java, influenced, Scala]
Generated description
Scala is a high-level, statically typed programming language that unifies object-oriented and functional programming paradigms and runs on the Java Virtual Machine.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Scala
Target entity description: Scala is a high-level, statically typed programming language that unifies object-oriented and functional programming paradigms and runs on the Java Virtual Machine.
  • A. 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.
  • B. F#
    F# is a functional-first, multi-paradigm programming language for the .NET platform, known for its strong type system and concise, expressive syntax.
  • C. Java
    Java is a large, densely populated island in Indonesia that has long served as the country’s political and economic center.
  • D. 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.
  • E. Julia
    Julia is a high-level, high-performance programming language designed for numerical computing, data science, and scientific research, combining the ease of dynamic languages with the speed of compiled languages.
  • F. None of above. chosen

Provenance (5 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_69a4933fa4d88190a7949cc83c08c5c1 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49b4c23548190a3b883239c7c78c8 completed March 1, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4ff4c3df48190a886a8d3c633d417 completed March 2, 2026, 3:09 a.m.
NEDg Description generation batch_69a4ffcad6e08190938018ade5bc5d67 completed March 2, 2026, 3:11 a.m.
NED2 Entity disambiguation (via description) batch_69a5001de9c481909d43c001028c922c completed March 2, 2026, 3:12 a.m.
Created at: March 1, 2026, 7:33 p.m.