Triple
T14396456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Outsell |
E356960
|
entity |
| Predicate | acquiredBy |
P347
|
FINISHED |
| Object | Zendesk |
E72313
|
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: Zendesk | Statement: [Outsell, acquiredBy, Zendesk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zendesk Context triple: [Outsell, acquiredBy, Zendesk]
-
A.
Zendesk
chosen
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.
-
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.
Zopim
Zopim is a live chat and customer messaging software platform that became part of Zendesk’s customer service product suite after its acquisition.
-
D.
ServiceNow
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.
-
E.
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.
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90826f908190b3969af9b7cf922f |
completed | April 14, 2026, 7:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe387f28688190b9d20f1e2bbc0ddc |
completed | May 8, 2026, 7:24 p.m. |
Created at: April 10, 2026, 1:17 a.m.