Triple
T20688314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steven Shih Chen |
E508480
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | PayPal |
—
|
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: PayPal | Statement: [Steven Shih Chen, employer, PayPal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PayPal Context triple: [Steven Shih Chen, employer, PayPal]
-
A.
PayPal
chosen
PayPal is a leading global online payment platform that enables individuals and businesses to send, receive, and manage digital payments securely over the internet.
-
B.
Paypay
Paypay is a coastal barangay in the municipality of Daanbantayan in Cebu, Philippines.
-
C.
Amazon Pay
Amazon Pay is a digital payment service that lets customers use their Amazon accounts to make secure purchases and payments on third-party websites and apps.
-
D.
WePay
WePay is an online payment services company that provides integrated payment processing solutions for platforms, marketplaces, and software providers.
-
E.
Stripe
Stripe is a leading financial technology company that provides online payment processing and related services for internet businesses worldwide.
- 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_69e0b4c1ed408190b72dd26b1e33f8a1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6c10b7b808190bdb8b08e53168fb8 |
completed | April 21, 2026, 12:12 a.m. |
Created at: April 16, 2026, 11:45 a.m.