Triple
T27663162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CAA |
E697169
|
entity |
| Predicate | recordExample |
P65225
|
FINISHED |
| Object | example.com. CAA 0 issue "letsencrypt.org" |
—
|
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: example.com. CAA 0 issue "letsencrypt.org" | Statement: [CAA, recordExample, example.com. CAA 0 issue "letsencrypt.org"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recordExample Context triple: [CAA, recordExample, example.com. CAA 0 issue "letsencrypt.org"]
-
A.
recordsObject
Indicates that one entity creates or maintains a record of another entity as its subject or content.
-
B.
recordDetail
chosen
Indicates that one entity stores or documents specific information or attributes about another entity.
-
C.
recordingOf
Indicates that one entity is an audio or video capture or performance that documents, represents, or preserves another entity (such as a work, event, or expression).
-
D.
recordsType
Indicates that one entity documents, stores, or keeps an official account of a particular type or category of information, event, or item.
-
E.
recorded
Indicates that one entity captured, stored, or documented information, audio, video, or data about another entity or event.
- 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_69ef590b85a4819083ec7c12bd3c9c10 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f6e6029a10819098ff21f58079e70e |
completed | May 3, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69f6e3d5e8188190b1e1c2e5d1b77031 |
completed | May 3, 2026, 5:57 a.m. |
Created at: April 27, 2026, 2:37 p.m.