Triple
T22566387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paychex |
E557961
|
entity |
| Predicate | offersProduct |
P10882
|
FINISHED |
| Object | Paychex Flex |
—
|
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: Paychex Flex | Statement: [Paychex, offersProduct, Paychex Flex]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paychex Flex Context triple: [Paychex, offersProduct, Paychex Flex]
-
A.
Paychex
chosen
Paychex is a leading American provider of payroll, human resources, and benefits outsourcing services for small to mid-sized businesses.
-
B.
Paylocity
Paylocity is a U.S.-based provider of cloud payroll and human capital management software solutions for businesses.
-
C.
Paycom
Paycom is a U.S.-based software company that provides cloud-based payroll and human capital management solutions to 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 Center
Paycom Center is a multi-purpose indoor arena in downtown Oklahoma City best known as the home of the NBA’s Oklahoma City Thunder.
- 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_69e11e5ae4ac8190b1f503457603d969 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15faaa0b081908d5aa8f3ba1e3dd3 |
completed | April 29, 2026, 1:32 a.m. |
Created at: April 16, 2026, 8:52 p.m.