Triple

T14321533
Position Surface form Disambiguated ID Type / Status
Subject David Flanagan E355100 entity
Predicate workedOn P3 FINISHED
Object SpiderMonkey JavaScript engine E24484 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: SpiderMonkey JavaScript engine | Statement: [David Flanagan, workedOn, SpiderMonkey JavaScript engine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SpiderMonkey JavaScript engine
Context triple: [David Flanagan, workedOn, SpiderMonkey JavaScript engine]
  • A. SpiderMonkey chosen
    SpiderMonkey is Mozilla's open-source JavaScript engine, written in C/C++ and used primarily in the Firefox web browser.
  • B. Rhino JavaScript engine
    Rhino JavaScript engine is an open-source JavaScript implementation written in Java that runs on the JVM and is used to execute JavaScript code within Java-based environments.
  • C. Hermes JavaScript engine
    Hermes JavaScript engine is a lightweight, high-performance JavaScript engine optimized for running React Native applications on mobile devices.
  • D. Nashorn
    Nashorn was a German World War II tank destroyer armed with a powerful 88 mm gun and built on a modified Panzer IV chassis.
  • E. JavaScriptCore
    JavaScriptCore is Apple’s high-performance JavaScript engine used primarily in the Safari web browser and WebKit-based applications.
  • 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_69d8278ed42c8190b9f882dcce611347 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de883bf71c8190a9a092a025cf98f0 completed April 14, 2026, 6:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd468e263c81909d7261bcfd949579 completed May 8, 2026, 2:12 a.m.
Created at: April 10, 2026, 1:13 a.m.