Triple
T14638612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lhazar |
E343666
|
entity |
| Predicate | religiousFigureTitle |
P70093
|
FINISHED |
| Object | shepherd-priests |
—
|
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: shepherd-priests | Statement: [Lhazar, religiousFigureTitle, shepherd-priests]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousFigureTitle Context triple: [Lhazar, religiousFigureTitle, shepherd-priests]
-
A.
religiousTitle
Indicates that one entity holds or is referred to by a specific religious rank, honorific, or clerical title in relation to another entity.
-
B.
religiousFigure
Indicates that one entity is recognized or designated as a religious leader, authority, or sacred person in relation to another entity.
-
C.
religiousFigureType
chosen
Indicates the specific role or category of a person recognized as a religious figure (e.g., priest, monk, prophet) within a religious context.
-
D.
ecclesiasticalTitleIncludes
Indicates that one ecclesiastical title contains, subsumes, or incorporates another ecclesiastical title as part of its designation or scope.
-
E.
honorsTitleOfSaint
Indicates that an entity recognizes or bestows the formal religious title of "saint" upon another entity.
- 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_69d822e1a2cc81908e5bb93cf61ce3cc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4aca6448190adf1042dfbfef716 |
completed | April 14, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69de657359c88190b082e3e9f86fc1d7 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:26 a.m.