Triple
T12099791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yaba |
E288160
|
entity |
| Predicate | hasTechCompanyPresence |
P17483
|
FINISHED |
| Object |
Paystack
Paystack is a Nigerian financial technology company that provides online payment processing solutions for businesses across Africa.
|
E963382
|
NE FINISHED |
How this triple was built (4 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: Paystack | Statement: [Yaba, hasTechCompanyPresence, Paystack]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paystack Context triple: [Yaba, hasTechCompanyPresence, Paystack]
-
A.
WePay
WePay is an online payment services company that provides integrated payment processing solutions for platforms, marketplaces, and software providers.
-
B.
Stripe
Stripe is a leading financial technology company that provides online payment processing and related services for internet businesses worldwide.
-
C.
Paypay
Paypay is a coastal barangay in the municipality of Daanbantayan in Cebu, Philippines.
-
D.
Pay.gov
Pay.gov is a U.S. government online payment portal that allows individuals and businesses to securely make electronic payments to federal agencies.
-
E.
Paymer
Paymer is a surname most notably associated with American character actor David Paymer, known for his extensive work in film and television.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Paystack Triple: [Yaba, hasTechCompanyPresence, Paystack]
Generated description
Paystack is a Nigerian financial technology company that provides online payment processing solutions for businesses across Africa.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Paystack Target entity description: Paystack is a Nigerian financial technology company that provides online payment processing solutions for businesses across Africa.
-
A.
WePay
WePay is an online payment services company that provides integrated payment processing solutions for platforms, marketplaces, and software providers.
-
B.
Stripe
Stripe is a leading financial technology company that provides online payment processing and related services for internet businesses worldwide.
-
C.
Paypay
Paypay is a coastal barangay in the municipality of Daanbantayan in Cebu, Philippines.
-
D.
Pay.gov
Pay.gov is a U.S. government online payment portal that allows individuals and businesses to securely make electronic payments to federal agencies.
-
E.
Paymer
Paymer is a surname most notably associated with American character actor David Paymer, known for his extensive work in film and television.
- F. None of above. chosen
Provenance (5 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_69d6ab4964708190850585628b287b0c |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91c5102848190ad652c3d6445f65a |
completed | April 10, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f6724de481909fe29e3278136ea2 |
completed | May 2, 2026, 1:04 p.m. |
| NEDg | Description generation | batch_69f5fe53d47c8190896a9abf8cc4bc31 |
completed | May 2, 2026, 1:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f5ffc2cfd08190b87eccd3a73afc77 |
completed | May 2, 2026, 1:44 p.m. |
Created at: April 8, 2026, 9:48 p.m.