Triple
T1031396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evan Williams |
E22258
|
entity |
| Predicate | coFounded |
P104
|
FINISHED |
| Object | Blogger |
E19881
|
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: Blogger | Statement: [Evan Williams, coFounded, Blogger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blogger Context triple: [Evan Williams, coFounded, Blogger]
-
A.
Blogger
chosen
Blogger is a popular online platform that allows users to create, publish, and manage personal or professional blogs on the web.
-
B.
Tumblr
Tumblr is a microblogging and social networking platform known for its highly customizable blogs, fandom communities, and viral multimedia content.
-
C.
Ning
Ning is an online platform that enables users and organizations to create their own custom social networks and communities.
-
D.
Automattic
Automattic is a web development and publishing company best known for owning and operating WordPress.com and several other major online platforms and tools.
-
E.
Google Sites
Google Sites is a web-based tool from Google that lets users easily create and share simple websites without needing to write code.
- 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_69a493d848848190aed4011b34b2e8d3 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b810429081908a97014ca740824b |
completed | March 1, 2026, 10:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac3bbf5a1c819086e1ff529d05f311 |
completed | March 7, 2026, 2:52 p.m. |
Created at: March 1, 2026, 7:41 p.m.