Triple

T1160477
Position Surface form Disambiguated ID Type / Status
Subject npm E24478 entity
Predicate usedWith P4791 FINISHED
Object Angular E34653 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: Angular | Statement: [npm, usedWith, Angular]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Angular
Context triple: [npm, usedWith, Angular]
  • A. Angular chosen
    Angular is a popular TypeScript-based open-source web application framework developed by Google for building dynamic, single-page client applications.
  • B. Vue.js
    Vue.js is a progressive JavaScript framework for building user interfaces and single-page applications with a focus on simplicity and reactive data binding.
  • C. Angolar
    Angolar is a Portuguese-based creole language spoken primarily by the Angolar community on the island of São Tomé in São Tomé and Príncipe.
  • D. NestJS
    NestJS is a progressive Node.js framework for building efficient, scalable server-side applications using TypeScript and a modular, dependency-injection-driven architecture.
  • E. Svelte
    Svelte is a modern JavaScript framework and compiler for building user interfaces that shifts much of the work to a build step, producing highly efficient, minimal runtime code.
  • 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_69a494060e148190abb42f971242c197 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bcaf3a9081908bad2eba74dffbc1 completed March 1, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac5ebbf80881909010e1e1e59212d4 completed March 7, 2026, 5:22 p.m.
Created at: March 1, 2026, 7:45 p.m.