Triple
T31306436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cherokee traditional religion |
E798344
|
entity |
| Predicate | hasViewOnIllness |
P112834
|
FINISHED |
| Object | imbalance between person and spiritual forces |
—
|
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: imbalance between person and spiritual forces | Statement: [Cherokee traditional religion, hasViewOnIllness, imbalance between person and spiritual forces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasViewOnIllness Context triple: [Cherokee traditional religion, hasViewOnIllness, imbalance between person and spiritual forces]
-
A.
viewOnIllness
chosen
Indicates the perspective, belief, or attitude that one entity holds about the nature, cause, or meaning of an illness affecting another entity.
-
B.
hasHealthConcern
Indicates that an entity has a specific health-related issue, condition, or concern associated with it.
-
C.
settingOfIllness
Indicates the context, environment, or circumstances in which an illness occurs or manifests.
-
D.
illness
Indicates that an entity is affected by, or suffering from, a particular disease or medical condition.
-
E.
hasPossibleSymptom
Indicates that an entity (such as a condition or disease) may be associated with a particular symptom that can potentially occur.
- 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_69f224e0bd4c8190aab9b29a73f7aa3c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fb3425666081908916fcbf3b5dd907 |
completed | May 6, 2026, 12:29 p.m. |
| PD | Predicate disambiguation | batch_69fb2f5f3164819099429c2cc3d24e01 |
completed | May 6, 2026, 12:09 p.m. |
Created at: April 29, 2026, 9:14 p.m.