Triple
T16189141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metera |
E392887
|
entity |
| Predicate | religiousEvidence |
P2154
|
FINISHED |
| Object | pre-Christian cult practices |
—
|
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: pre-Christian cult practices | Statement: [Metera, religiousEvidence, pre-Christian cult practices]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousEvidence Context triple: [Metera, religiousEvidence, pre-Christian cult practices]
-
A.
religiousElement
chosen
Indicates that something is a component, aspect, or feature associated with a religion or religious practice.
-
B.
religiousTextOf
Indicates that one entity is a religious text that is sacred to, foundational for, or primarily associated with another entity (such as a religion, denomination, or faith community).
-
C.
religiousTopicAddressed
Indicates that a subject deals with, discusses, or focuses on a religious theme, issue, or question.
-
D.
religiousTextType
Indicates that one entity is a religious text and specifies the type or category of that religious text in relation to the other entity.
-
E.
religiousTextCategory
Indicates that a religious text belongs to or is classified under a particular category or type.
- 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e222d3a8e48190bdf29a633f4b0490 |
completed | April 17, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69e219e11f6081909106b1240a17fd37 |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:02 a.m.