Triple
T10110499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject |
E218225
|
entity | |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | WeChat Pay |
E218225
|
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: WeChat Pay | Statement: [WeChat, hasComponent, WeChat Pay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WeChat Pay Context triple: [WeChat, hasComponent, WeChat Pay]
-
A.
MobilePay
MobilePay is a popular Nordic mobile payment app that allows users to send and receive money, pay in stores and online, and manage everyday transactions via their smartphones.
-
B.
WeChat
chosen
WeChat is a Chinese multi-purpose mobile app developed by Tencent that combines messaging, social media, and payment services into a single platform.
-
C.
GrabPay
GrabPay is Grab’s digital wallet and mobile payment service used for cashless transactions across transport, food delivery, and everyday purchases in Southeast Asia.
-
D.
GoPay
GoPay is a leading Indonesian digital wallet and payment platform that enables users to make cashless transactions for online and offline services, including ride-hailing, food delivery, and bill payments.
-
E.
UnionPay
UnionPay is a Chinese state-backed financial services corporation best known for operating one of the world’s largest bank card and payment networks.
- 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_69ca83da93fc8190b54e44bc2b34857c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd0cf39908190bba679ace095eefc |
completed | April 2, 2026, 2:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2cc1805d08190bc39aadf1e84a569 |
completed | April 5, 2026, 8:54 p.m. |
Created at: March 30, 2026, 9:03 p.m.