Triple
T23182463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Square |
E579498
|
entity |
| Predicate | product |
P490
|
FINISHED |
| Object | Square Payroll |
—
|
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: Square Payroll | Statement: [Square, product, Square Payroll]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Square Payroll Context triple: [Square, product, Square Payroll]
-
A.
Square Payroll
chosen
Square Payroll is a cloud-based payroll service designed for small and medium-sized businesses to manage employee and contractor payments, tax filings, and compliance.
-
B.
Paylocity
Paylocity is a U.S.-based provider of cloud payroll and human capital management software solutions for businesses.
-
C.
Paychex
Paychex is a leading American provider of payroll, human resources, and benefits outsourcing services for small to mid-sized businesses.
-
D.
Paycor, Inc.
Paycor, Inc. is a U.S.-based provider of human capital management and payroll software solutions for small and midsize businesses.
-
E.
Paycom
Paycom is a U.S.-based software company that provides cloud-based payroll and human capital management solutions to businesses.
- 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_69e245ff8000819090d12008805315b7 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f705c14819082c8580a03ed6286 |
completed | April 29, 2026, 4:56 a.m. |
Created at: April 17, 2026, 4:05 p.m.