Triple
T6681706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | .ge |
E151996
|
entity |
| Predicate | technicalContactType |
P12914
|
FINISHED |
| Object | registry operator |
—
|
LITERAL 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: registry operator | Statement: [.ge, technicalContactType, registry operator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: technicalContactType Context triple: [.ge, technicalContactType, registry operator]
-
A.
technicalContact
Indicates that one entity serves as the primary point of contact for technical issues, support, or maintenance related to another entity.
-
B.
hasContactType
chosen
Indicates the specific kind or category of contact relationship that exists between two entities.
-
C.
contactWith
Indicates that two entities are in direct or indirect physical or communicative interaction or touch with each other.
-
D.
administrativeContact
Indicates that one entity serves as the primary administrative point of contact or manager responsible for handling administrative matters related to another entity.
-
E.
contactLanguageWith
Indicates that two entities communicate with each other using a particular language as the medium of contact.
- F. None of above.
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_69c687f9977c819097e7f5ada4fe522e |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c0aa8c5c8190a302b261f11b70cb |
completed | March 27, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c6ad0b6d00819086205b8ce30dd045 |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:04 p.m.