Triple
T32582351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RFC 7218 |
E832822
|
entity |
| Predicate | updatesUsageOf |
P174924
|
FINISHED |
| Object | TLSA resource records |
—
|
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: TLSA resource records | Statement: [RFC 7218, updatesUsageOf, TLSA resource records]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: updatesUsageOf Context triple: [RFC 7218, updatesUsageOf, TLSA resource records]
-
A.
trackUsage
Indicates that one entity monitors and records how another entity or resource is being used over time.
-
B.
usageAmong
Indicates how frequently or in what manner something is used within a particular group, context, or population.
-
C.
exportUse
Indicates that something is used, intended, or suitable for export from one place or market to another.
-
D.
updateFor
Indicates that one entity is modified or refreshed in response to changes or conditions associated with another entity.
-
E.
tracksUsage
Indicates that one entity monitors, records, or keeps a log of how another entity is used over time.
- 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_69f349289adc81909f4374a58ec35a39 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c90790788190a1ed09adc86ed22d |
completed | May 3, 2026, 4:03 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f42fbc8190a06eb1044c9e6094 |
completed | May 3, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f6c814c26c81908f5c47285129ff2a |
completed | May 3, 2026, 3:59 a.m. |
Created at: May 1, 2026, 1:04 a.m.