Triple

T5233032
Position Surface form Disambiguated ID Type / Status
Subject Doctrine of the Mean E118153 entity
Predicate relatedWork P37 FINISHED
Object Great Learning E118152 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: Great Learning | Statement: [Doctrine of the Mean, relatedWork, Great Learning]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Great Learning
Context triple: [Doctrine of the Mean, relatedWork, Great Learning]
  • A. Great Learning chosen
    Great Learning is a foundational Confucian classic that outlines principles of moral self-cultivation and good governance.
  • B. Udacity
    Udacity is an online learning platform specializing in technology-focused courses and career-oriented "Nanodegree" programs developed in collaboration with industry partners.
  • C. Coursera
    Coursera is a major online learning platform that partners with universities and organizations worldwide to offer courses, professional certificates, and degree programs across a wide range of subjects.
  • D. Udemy
    Udemy is a global online learning platform that hosts a vast marketplace of video-based courses across diverse subjects for learners and professionals.
  • E. FutureLearn
    FutureLearn is a digital education platform that partners with universities and institutions worldwide to deliver a wide range of online courses and learning programs.
  • 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_69bd4466fb8c819083b806a79414d7e4 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7b0389048190b55b7c44fe657044 completed March 20, 2026, 4:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69bef8154940819098ed76e14804f4b3 completed March 21, 2026, 7:57 p.m.
Created at: March 20, 2026, 1:49 p.m.