Triple

T9838329
Position Surface form Disambiguated ID Type / Status
Subject Deeplearning.ai E239157 entity
Predicate collaboratesWith P37 FINISHED
Object Coursera E9162 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: Coursera | Statement: [Deeplearning.ai, collaboratesWith, Coursera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Coursera
Context triple: [Deeplearning.ai, collaboratesWith, Coursera]
  • A. Coursera chosen
    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.
  • B. edX
    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.
  • C. Udacity
    Udacity is an online learning platform specializing in technology-focused courses and career-oriented "Nanodegree" programs developed in collaboration with industry partners.
  • 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_69ca84e314108190978324a4bdb959f8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb34921b881909836ba0f5b42a27b completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20d4079048190976eb198f8ef62f0 completed April 5, 2026, 7:20 a.m.
Created at: March 30, 2026, 8:33 p.m.