Triple
T7297476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Mockapetris |
E164560
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Nominum |
E37205
|
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: Nominum | Statement: [Paul Mockapetris, employer, Nominum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nominum Context triple: [Paul Mockapetris, employer, Nominum]
-
A.
Namesys
Namesys was a software company best known for developing the ReiserFS journaling file system for Linux.
-
B.
Norid
Norid is the Norwegian registry responsible for administering the country’s .no top-level internet domain.
-
C.
Nortone
Nortone is an alternative spelling of the name Norton, which is used as both a surname and a place name in English-speaking regions.
-
D.
Golin
Golin is a surname most notably associated with American film and television producer Steve Golin, founder of the production company Anonymous Content.
-
E.
VeriSign
chosen
VeriSign is an American technology company best known for operating key internet infrastructure, including managing the .com and .net top-level domains and providing critical DNS and security services.
- 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_69c6887a499881909dd23341399c59d8 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6eb8e48d48190ada4d507f3b61bc4 |
completed | March 27, 2026, 8:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7e54c25c88190891311b72f242e86 |
completed | March 28, 2026, 2:27 p.m. |
Created at: March 27, 2026, 3 p.m.