Triple
T20903199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fred Luddy |
E514723
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | ServiceNow |
—
|
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: ServiceNow | Statement: [Fred Luddy, employer, ServiceNow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ServiceNow Context triple: [Fred Luddy, employer, ServiceNow]
-
A.
ServiceNow
chosen
ServiceNow is a cloud-based software company best known for its enterprise workflow and IT service management platform that helps organizations automate and streamline business processes.
-
B.
Zoho Desk
Zoho Desk is a cloud-based customer service and help desk software platform designed to help businesses manage and streamline their support operations across multiple channels.
-
C.
PagerDuty
PagerDuty is a cloud-based incident management and alerting platform that helps IT and DevOps teams detect, triage, and resolve operational issues in real time.
-
D.
Zendesk
Zendesk is a customer service and engagement software company best known for its cloud-based help desk and support ticketing solutions used by businesses worldwide.
-
E.
Service Cloud
Service Cloud is Salesforce’s customer service and support platform that helps organizations manage and resolve customer inquiries across multiple channels.
- 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_69e0b4f8a1108190bce3d31331290ced |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6e8fd7e4481909088b7f74ba24549 |
completed | April 21, 2026, 3:03 a.m. |
Created at: April 16, 2026, 12:47 p.m.