Triple
T20233267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christian Science practitioner |
E495584
|
entity |
| Predicate | healingApproach |
P130966
|
FINISHED |
| Object | non-medical |
—
|
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: non-medical | Statement: [Christian Science practitioner, healingApproach, non-medical]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: healingApproach Context triple: [Christian Science practitioner, healingApproach, non-medical]
-
A.
typeOfHealing
chosen
Indicates the specific method or modality by which a healing process is carried out or achieved.
-
B.
therapeuticOrientation
Indicates the specific therapeutic approach or framework a practitioner uses when providing psychological or counseling treatment.
-
C.
alternativeTreatmentOf
Indicates that one treatment serves as an alternative option to another treatment for addressing the same or a related condition or problem.
-
D.
approaches
Indicates that one entity moves closer in position or state to another entity or reference point.
-
E.
initialRemedy
Indicates that a particular remedy is the first or primary treatment applied or prescribed in response to a condition or problem.
- 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_69da626cff80819097b530718a7c98b6 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e67166d4d081908c4b8eeb66e7e090 |
completed | April 20, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69e55b18609481909ab28bc8750a642f |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:40 p.m.