Triple
T7931047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DocuSign |
E184188
|
entity |
| Predicate | offers |
P178
|
FINISHED |
| Object | DocuSign Notary |
E184188
|
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: DocuSign Notary | Statement: [DocuSign, offers, DocuSign Notary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DocuSign Notary Context triple: [DocuSign, offers, DocuSign Notary]
-
A.
DocuSign
chosen
DocuSign is a leading electronic signature and digital transaction management company that enables users to securely sign, send, and manage documents online.
-
B.
HelloSign
HelloSign is an electronic signature and digital document workflow platform that enables users to sign, send, and manage legally binding documents online.
-
C.
DocSend
DocSend is a document-sharing and tracking platform designed for securely sending files and gaining analytics on how recipients engage with them.
-
D.
docuverse
Docuverse is Ted Nelson’s visionary concept of a universal, interconnected digital library where all documents are permanently linked and traceable across a global hypertext system.
-
E.
Adobe Document Cloud
Adobe Document Cloud is Adobe’s integrated suite of cloud-based services and apps for creating, editing, managing, and securely sharing PDF documents across devices.
- 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_69ca8290c21c8190906a5ca6fe2b03c4 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3accc388819087065ebe7d5d9591 |
completed | March 31, 2026, 3:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5c01602081908ea1af24785260ff |
completed | March 31, 2026, 5:30 a.m. |
Created at: March 30, 2026, 5:07 p.m.