Triple
T6308253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phil Zimmermann |
E141432
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Pretty Good Privacy |
E35340
|
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: Pretty Good Privacy | Statement: [Phil Zimmermann, notableWork, Pretty Good Privacy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pretty Good Privacy Context triple: [Phil Zimmermann, notableWork, Pretty Good Privacy]
-
A.
PGP
chosen
PGP (Pretty Good Privacy) is an encryption program that provides cryptographic privacy and authentication for data communication, most notably for securing emails and files.
-
B.
GNU Privacy Guard
GNU Privacy Guard is a free, open-source implementation of the OpenPGP standard used for encrypting and signing data and communications.
-
C.
S/MIME
S/MIME is a widely used standard for secure email that provides encryption and digital signatures using public key cryptography.
-
D.
Gpg4win
Gpg4win is a Windows software suite for email and file encryption that provides an easy-to-use implementation of OpenPGP and S/MIME.
-
E.
Postel
Postel is a surname most prominently associated with Jon Postel, a pioneering computer scientist and key architect of the early Internet.
- 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_69c008d00efc8190a36c05b4b4a3bf4b |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0647d38008190abaf96632712ddf9 |
completed | March 22, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5e45330ec8190945682962ae823b0 |
completed | March 27, 2026, 1:58 a.m. |
Created at: March 22, 2026, 4:28 p.m.