Triple
T10151520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dave Moellenhoff |
E232652
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Salesforce |
E17666
|
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: Salesforce | Statement: [Dave Moellenhoff, associatedWith, Salesforce]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Salesforce Context triple: [Dave Moellenhoff, associatedWith, Salesforce]
-
A.
Salesforce
chosen
Salesforce is a leading cloud-based customer relationship management (CRM) company known for its suite of enterprise applications for sales, service, marketing, and analytics.
-
B.
Zoho CRM
Zoho CRM is a cloud-based customer relationship management platform designed to help businesses manage sales, marketing, and customer support in a unified system.
-
C.
SDFC
SDFC is the commonly used abbreviation for San Diego FC, a professional soccer club based in San Diego, California.
-
D.
Gainsight
Gainsight is a customer success and product experience software company known for helping businesses reduce churn, drive expansion, and improve customer retention through data-driven insights and workflows.
-
E.
ReadyForce
ReadyForce is a career networking and recruiting platform that connects students and recent graduates with employers, particularly in the tech and startup sectors.
- 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_69ca84885e48819088a31b127cf44904 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdec0584a48190b65daa8370555c27 |
completed | April 2, 2026, 4:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d300a40638819082e575d957711377 |
completed | April 6, 2026, 12:39 a.m. |
Created at: March 30, 2026, 9:08 p.m.