Triple
T22748076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Municipality of Daanbantayan |
E562608
|
entity |
| Predicate | hasBarangay |
P29835
|
FINISHED |
| Object | Paypay |
—
|
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: Paypay | Statement: [Municipality of Daanbantayan, hasBarangay, Paypay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paypay Context triple: [Municipality of Daanbantayan, hasBarangay, Paypay]
-
A.
Paypay
chosen
Paypay is a coastal barangay in the municipality of Daanbantayan in Cebu, Philippines.
-
B.
WePay
WePay is an online payment services company that provides integrated payment processing solutions for platforms, marketplaces, and software providers.
-
C.
PAYX
PAYX is the stock ticker symbol for Paychex, Inc., a major U.S.-based provider of payroll, human resources, and benefits outsourcing services.
-
D.
PayPay
PayPay is a Japanese mobile payment and digital wallet service widely used for cashless transactions across Japan.
-
E.
PayPal
PayPal is a leading global online payment platform that enables individuals and businesses to send, receive, and manage digital payments securely over the internet.
- 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_69e245513a5c81908d5cb471b4fc429d |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f179b702388190b134dde5f80ea3cd |
completed | April 29, 2026, 3:23 a.m. |
Created at: April 17, 2026, 3:24 p.m.