Triple
T23425406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Can Has Cheezburger? |
E560779
|
entity |
| Predicate | acquiredBy |
P347
|
FINISHED |
| Object | Ben Huh |
—
|
NE NERFINISHED |
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: Ben Huh | Statement: [I Can Has Cheezburger?, acquiredBy, Ben Huh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ben Huh Context triple: [I Can Has Cheezburger?, acquiredBy, Ben Huh]
-
A.
Ben Huh
chosen
Ben Huh is a Korean-American entrepreneur best known as the former CEO of the Cheezburger Network, a pioneering humor and meme website company.
-
B.
Matthew Hoh
Matthew Hoh is a former U.S. Marine and State Department official known for his principled resignation over the Afghanistan War and subsequent antiwar activism.
-
C.
Chris Wang
Chris Wang is an entrepreneur best known as a co-founder and former CEO of the social gaming company Playdom.
-
D.
Frank Wang
Frank Wang is a Chinese entrepreneur and engineer best known as the founder and CEO of DJI, the world’s leading consumer drone manufacturer.
-
E.
Greg Universe
Greg Universe is the easygoing, music-loving human father of Steven Universe in the animated series "Steven Universe."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2454cb1108190ab21ada5411a7146 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a54951688190a3c5382971af3e41 |
completed | April 29, 2026, 6:29 a.m. |
Created at: April 17, 2026, 5:47 p.m.