Triple
T1877937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinese folk religion |
E39185
|
entity |
| Predicate | hasRitualSpecialist |
P17182
|
FINISHED |
| Object | spirit medium |
—
|
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: spirit medium | Statement: [Chinese folk religion, hasRitualSpecialist, spirit medium]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRitualSpecialist Context triple: [Chinese folk religion, hasRitualSpecialist, spirit medium]
-
A.
hasRitual
Indicates that an entity performs, observes, or is associated with a specific ritual or ceremonial practice.
-
B.
hasRitualSpace
Indicates that an entity possesses or is associated with a designated space used for ritual or ceremonial activities.
-
C.
hasRitualFocus
Indicates that an entity is associated with or directed toward a particular object, practice, or element that serves as the central focus of a ritual.
-
D.
hasRitualObject
Indicates that an entity possesses, uses, or is associated with an object specifically employed in a ritual or ceremonial context.
-
E.
ritualSpecialist
chosen
Indicates that one entity serves as a designated expert or practitioner responsible for performing or overseeing rituals in relation to another entity or 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_69a8862f7074819096afe7fe65e179e9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb0f79fbc819085c54f3189a552d9 |
completed | March 7, 2026, 5 a.m. |
| PD | Predicate disambiguation | batch_69abafe2b56c81909e13d543982e6e13 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:34 p.m.