Triple
T5533473
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uniform Domain Name Dispute Resolution Policy |
E145103
|
entity |
| Predicate | possibleRemedy |
P2242
|
FINISHED |
| Object | cancellation of the domain name |
—
|
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: cancellation of the domain name | Statement: [Uniform Domain Name Dispute Resolution Policy, possibleRemedy, cancellation of the domain name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: possibleRemedy Context triple: [Uniform Domain Name Dispute Resolution Policy, possibleRemedy, cancellation of the domain name]
-
A.
remedy
Indicates that one entity serves to cure, alleviate, or counteract a problem, illness, or undesirable condition affecting another entity.
-
B.
remedySought
chosen
Indicates that a particular legal or corrective action is being requested as a solution or relief in response to a problem or dispute.
-
C.
typeOfRemedy
Indicates that one entity is a specific kind or category of remedy in relation to another entity.
-
D.
treats
Indicates that one entity provides medical care or therapeutic intervention to another entity.
-
E.
exportTreatment
Indicates the action or process of sending or transferring a treatment (such as a medical, data, or procedural treatment) from one system, location, or context to another for external use or application.
- 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_69c008f9955881909bfa8348b56b4739 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f9ea2c88190a68642f5799bd8ff |
completed | March 22, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69c01b0c50e48190a1b03ecd20ca440b |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:34 p.m.