Triple
T168882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | YES Network |
E3074
|
entity |
| Predicate | owner |
P347
|
FINISHED |
| Object | Amazon |
E4942
|
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: Amazon | Statement: [YES Network, owner, Amazon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amazon Context triple: [YES Network, owner, Amazon]
-
A.
Amazon
chosen
Amazon is a multinational technology and e-commerce company best known for its vast online marketplace, cloud computing services through AWS, and significant influence on global retail and logistics.
-
B.
X.com
X.com is an online financial services and payments company co-founded by Elon Musk in 1999 that later became part of PayPal.
-
C.
Costco Wholesale Corporation
Costco Wholesale Corporation is a multinational membership-based warehouse club retailer known for selling bulk goods at discounted prices through large-scale warehouse stores.
-
D.
eBay
eBay is a global e-commerce company best known for its online auction and consumer-to-consumer sales platform.
-
E.
United Parcel Service (UPS)
United Parcel Service (UPS) is a global package delivery and supply chain management company known for its extensive logistics network and brown delivery trucks.
- 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_69a2524ce1e48190ab066bf72859f474 |
completed | Feb. 28, 2026, 2:26 a.m. |
| NER | Named-entity recognition | batch_69a258b6f4f88190b1264bbbeb19a29e |
completed | Feb. 28, 2026, 2:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2e0f8bf748190b2752f250a63d8e3 |
completed | Feb. 28, 2026, 12:35 p.m. |
Created at: Feb. 28, 2026, 2:34 a.m.