Triple
T287297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Domain Name System root zone |
E5910
|
entity |
| Predicate | hasUpdateFrequency |
P7407
|
FINISHED |
| Object | multiple times per day as needed |
—
|
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: multiple times per day as needed | Statement: [Domain Name System root zone, hasUpdateFrequency, multiple times per day as needed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUpdateFrequency Context triple: [Domain Name System root zone, hasUpdateFrequency, multiple times per day as needed]
-
A.
hasUpdatePolicy
Indicates that one entity defines or is associated with the rules or strategy governing how another entity is updated or maintained over time.
-
B.
tienePeriodicidad
chosen
Indicates that something occurs, recurs, or is scheduled with a specific regular frequency or periodic pattern.
-
C.
hasLeapYearFrequency
Indicates how often leap years occur within a given temporal pattern or calendar system.
-
D.
isUpdated
Indicates that an entity has been modified or brought to a more recent state compared to its previous version or a reference point.
-
E.
awardedFrequency
Indicates how often an award or recognition is given within a specified time period.
- 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_69a25946a7ac8190a78871c210213272 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NER | Named-entity recognition | batch_69a25e2ddaa88190b08c40b5823f30a0 |
completed | Feb. 28, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69a25b7c1448819082064f474633acd5 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 3:02 a.m.