Triple
T23883905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sacred Round |
E600278
|
entity |
| Predicate | practitionerTitle |
P153933
|
FINISHED |
| Object | daykeeper |
—
|
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: daykeeper | Statement: [Sacred Round, practitionerTitle, daykeeper]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: practitionerTitle Context triple: [Sacred Round, practitionerTitle, daykeeper]
-
A.
practitionerType
Indicates the specific category or role of practitioner associated with an entity (e.g., doctor, nurse, therapist).
-
B.
professionalName
Indicates the formal name or title an entity uses in a professional or occupational context.
-
C.
professionalTitleAbbreviation
Indicates that one entity is an abbreviated form of a professional title associated with another entity.
-
D.
professionalTitleAfterCompletion
Indicates that an entity is granted or holds a specific professional title as a result of successfully completing a particular program, course, or qualification.
-
E.
academicTitleOf
Indicates that one entity is the academic title or rank held by another entity.
- 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_69e295318e148190b9979d8fc02e168f |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1ccfbbe4c819093e590709719ab72 |
completed | April 29, 2026, 9:18 a.m. |
| PD | Predicate disambiguation | batch_69f1614e24b48190a1c8fb5b7c75ee0f |
completed | April 29, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f167dca3608190ace9d2eef56b2af6 |
completed | April 29, 2026, 2:07 a.m. |
Created at: April 17, 2026, 8:24 p.m.