Triple

T19494983
Position Surface form Disambiguated ID Type / Status
Subject Office of Digital Learning at MIT E487744 entity
Predicate usesPlatform P1292 FINISHED
Object edX NE NERFINISHED

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: edX | Statement: [Office of Digital Learning at MIT, usesPlatform, edX]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: edX
Context triple: [Office of Digital Learning at MIT, usesPlatform, edX]
  • A. edX chosen
    edX is a leading online learning platform founded by MIT and Harvard that offers university-level courses, professional certificates, and degree programs to learners worldwide.
  • B. 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.
  • C. 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.
  • D. Udacity
    Udacity is an online learning platform specializing in technology-focused courses and career-oriented "Nanodegree" programs developed in collaboration with industry partners.
  • E. Udemy
    Udemy is a global online learning platform that hosts a vast marketplace of video-based courses across diverse subjects for learners and professionals.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d9d1c88190b01cd78b8be49384 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63490c16481908423e304d82722d7 completed April 20, 2026, 2:13 p.m.
Created at: April 10, 2026, 1:40 p.m.