Triple
T10542437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lynda Resnick |
E248729
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Lynda |
E607467
|
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: Lynda | Statement: [Lynda Resnick, givenName, Lynda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lynda Context triple: [Lynda Resnick, givenName, Lynda]
-
A.
Lynda
chosen
Lynda is a feminine given name, often considered a variant of Linda, that gained popularity in English-speaking countries in the mid-20th century.
-
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.
LinkedIn Learning
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.
-
D.
O'Reilly Online Learning platform
O'Reilly Online Learning platform is a subscription-based digital learning service offering technical and business content such as books, videos, and interactive courses for professionals.
-
E.
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.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5190f46d08190a92b1191881ffb92 |
completed | April 7, 2026, 2:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d9342e6cf48190b0ca53ff2a4e0214 |
completed | April 10, 2026, 5:32 p.m. |
Created at: April 6, 2026, 12:32 p.m.