Triple
T11579975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Umbanda |
E274598
|
entity |
| Predicate | hasSacredTextStatus |
P86758
|
FINISHED |
| Object | no single canonical scripture |
—
|
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: no single canonical scripture | Statement: [Umbanda, hasSacredTextStatus, no single canonical scripture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSacredTextStatus Context triple: [Umbanda, hasSacredTextStatus, no single canonical scripture]
-
A.
hasSacredText
Indicates that an entity possesses or is associated with a particular sacred or religious text.
-
B.
sacredTextStatus
chosen
Indicates the status or classification of a text in terms of its recognized sacredness or religious authority within a tradition.
-
C.
sacredLanguageStatus
Indicates that a language holds a recognized sacred or liturgical status within a religious or spiritual tradition.
-
D.
hasLiturgicalTexts
Indicates that an entity possesses or is associated with specific liturgical texts used in religious worship or ceremonies.
-
E.
hasLiturgicalBook
Indicates that one entity possesses, uses, or is associated with a specific liturgical book in a religious or worship context.
- 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_69d6aae5ac3c81908d2b0a3a665665b2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8904c51b881909e7be84c6f3de79f |
completed | April 10, 2026, 5:53 a.m. |
| PD | Predicate disambiguation | batch_69d85dcbacd0819094d4a1237055affa |
completed | April 10, 2026, 2:17 a.m. |
Created at: April 8, 2026, 9:38 p.m.