Triple
T10862470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | .sx |
E256438
|
entity |
| Predicate | previousSharedTLD |
P96124
|
FINISHED |
| Object | .an |
—
|
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: .an | Statement: [.sx, previousSharedTLD, .an]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: previousSharedTLD Context triple: [.sx, previousSharedTLD, .an]
-
A.
TLDType
Indicates the classification or category of a top-level domain (TLD) based on its intended purpose or administrative type.
-
B.
formerDomain
Indicates that one entity was previously the domain or area of control, influence, or ownership of another entity, but no longer is.
-
C.
previousSharedDivision
Indicates that two entities have both belonged to or participated in the same division at some earlier point in time.
-
D.
relatedTLD
Indicates that one top-level domain (TLD) has an association or connection with another TLD, such as similarity, shared purpose, or contextual relevance.
-
E.
laterDomain
Indicates that one domain or time interval occurs strictly after another in a temporal ordering.
- F. None of above. chosen
Provenance (4 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_69d6aa83d1448190a66d93c32394d21f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7515238108190a72eb8cd147f223d |
completed | April 9, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69d70d308dfc81908792f98cfb871392 |
completed | April 9, 2026, 2:21 a.m. |
| PDg | Predicate description generation | batch_69d7101c96708190808fef73199e8482 |
completed | April 9, 2026, 2:34 a.m. |
Created at: April 8, 2026, 9:20 p.m.