Triple
T10151511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salesforce |
E232652
|
entity |
| Predicate | coFounder |
P2835
|
FINISHED |
| Object | Dave Moellenhoff |
E232652
|
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: Dave Moellenhoff | Statement: [Salesforce, coFounder, Dave Moellenhoff]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dave Moellenhoff Context triple: [Salesforce, coFounder, Dave Moellenhoff]
-
A.
Dave Moellenhoff
chosen
Dave Moellenhoff is a software engineer and entrepreneur best known as one of the original co-founders and early technical leaders of Salesforce.
-
B.
Dave Moffenbeier
Dave Moffenbeier is a technology entrepreneur best known as a co-founder of the electronic design automation company Mentor Graphics.
-
C.
Dave Holstein
Dave Holstein is a television and film writer best known for his work on series like "Kidding" and contributions to major animated features such as "Inside Out 2."
-
D.
Kevin Nolting
Kevin Nolting is an American film editor best known for his work on Pixar animated features, including the Academy Award-winning film "Up."
-
E.
Michael Schoeffling
Michael Schoeffling is an American former actor and model best known for his role as Jake Ryan in the 1984 film "Sixteen Candles."
- 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_69e5561714a081909cbf1cc7d5d0ac0a |
completed | April 19, 2026, 10:24 p.m. |
Created at: March 30, 2026, 9:08 p.m.