Triple
T374254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marc Andreessen |
E8334
|
entity |
| Predicate | founded |
P104
|
FINISHED |
| Object | Ning |
E47371
|
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: Ning | Statement: [Marc Andreessen, founded, Ning]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ning Context triple: [Marc Andreessen, founded, Ning]
-
A.
Ning
chosen
Ning is an online platform that enables users and organizations to create their own custom social networks and communities.
-
B.
Tumblr
Tumblr is a microblogging and social networking platform known for its highly customizable blogs, fandom communities, and viral multimedia content.
-
C.
MySpace
MySpace is a pioneering early-2000s social networking website that allowed users to create customizable profile pages, connect with friends, and share music and other media.
-
D.
Sakai
Sakai is a major Japanese city in Osaka Prefecture known historically as a prosperous port and merchant center and today as an important industrial and cultural hub.
-
E.
Sugar Labs
Sugar Labs is a nonprofit organization that develops and maintains the Sugar learning platform, an open-source educational software environment originally created for the One Laptop per Child project.
- 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_69a2e7f2ec648190b42bc7db424f8109 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec13b9b48190b294d998c6720132 |
completed | Feb. 28, 2026, 1:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3f4da5b2881909f71546e714c7883 |
completed | March 1, 2026, 8:12 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.