Triple
T20150169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spy magazine |
E491413
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object | Gawker |
—
|
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: Gawker | Statement: [Spy magazine, influenced, Gawker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gawker Context triple: [Spy magazine, influenced, Gawker]
-
A.
Gawker Media
chosen
Gawker Media was a now-defunct American online media company known for its network of influential blogs covering gossip, technology, feminism, and pop culture.
-
B.
Cheezburger Network
Cheezburger Network is a humor and entertainment website network best known for hosting viral meme and image macro sites like I Can Has Cheezburger?.
-
C.
Gizmodo
Gizmodo is a technology and design-focused news and opinion website known for its coverage of gadgets, science, and digital culture.
-
D.
The Onion
The Onion is a distinctive, modernist London building known for its layered, bulb-like architectural design that resembles the shape of an onion.
-
E.
Huffington
Huffington is the surname of Arianna Huffington, the Greek-American author, media entrepreneur, and co-founder of The Huffington Post.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667a1c5848190975b17ab07251f8b |
completed | April 20, 2026, 5:51 p.m. |
Created at: April 11, 2026, 11:33 p.m.