Triple

T264705
Position Surface form Disambiguated ID Type / Status
Subject LinkedIn E5698 entity
Predicate product P490 FINISHED
Object LinkedIn Learning E34621 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: LinkedIn Learning | Statement: [LinkedIn, product, LinkedIn Learning]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LinkedIn Learning
Context triple: [LinkedIn, product, LinkedIn Learning]
  • A. LinkedIn Learning chosen
    LinkedIn Learning is an online educational platform offering video-based courses in business, technology, and creative skills, integrated with LinkedIn for professional development and career growth.
  • B. Udemy
    Udemy is a global online learning platform that hosts a vast marketplace of video-based courses across diverse subjects for learners and professionals.
  • 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. OpenLearning
    OpenLearning is an online education platform that hosts and delivers massive open online courses (MOOCs) from institutions and educators worldwide.
  • 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_69a2587daeb081909591b9d30f80a271 completed Feb. 28, 2026, 2:52 a.m.
NER Named-entity recognition batch_69a25d8f9bbc8190a13841e4de093a66 completed Feb. 28, 2026, 3:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69a38b8e36b481909f9a039236e663df completed March 1, 2026, 12:42 a.m.
Created at: Feb. 28, 2026, 2:56 a.m.