Triple
T2692198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haitian Vodou |
E58427
|
entity |
| Predicate | hasSacredTextForm |
P6480
|
FINISHED |
| Object | oral tradition |
—
|
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: oral tradition | Statement: [Haitian Vodou, hasSacredTextForm, oral tradition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSacredTextForm Context triple: [Haitian Vodou, hasSacredTextForm, oral tradition]
-
A.
hasSacredText
Indicates that an entity possesses or is associated with a particular sacred or religious text.
-
B.
hasLiteraryForm
chosen
Indicates that one entity is expressed, structured, or realized in a particular literary form (such as a genre, style, or textual format).
-
C.
sacredLanguageStatus
Indicates that a language holds a recognized sacred or liturgical status within a religious or spiritual tradition.
-
D.
hasLiturgicalBook
Indicates that one entity possesses, uses, or is associated with a specific liturgical book in a religious or worship context.
-
E.
usedForReligiousTexts
Indicates that something is used in the creation, preservation, or practice of religious texts or scriptures.
- 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_69ab4ac269e481909cb317d79e68b75b |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda0dd97c81909a60cf200f57c087 |
completed | March 7, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69abd81ea5d88190ab5c8f8b8064b931 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:54 p.m.