Triple
T13131984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | bimaristan |
E311984
|
entity |
| Predicate | practicedMedicineOfTradition |
P108232
|
FINISHED |
| Object | Islamic medicine |
—
|
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: Islamic medicine | Statement: [bimaristan, practicedMedicineOfTradition, Islamic medicine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: practicedMedicineOfTradition Context triple: [bimaristan, practicedMedicineOfTradition, Islamic medicine]
-
A.
practicedTradition
Indicates that an entity engages in or carries out a particular tradition as a customary or repeated practice.
-
B.
practicedMedicineIn
Indicates that a person engaged in the professional practice of medicine within a specified location or jurisdiction.
-
C.
cultPractices
Indicates involvement in or performance of rituals, beliefs, or behaviors associated with a cult.
-
D.
followedPracticeOf
Indicates that one entity adopted, adhered to, or modeled its behavior, methods, or customs after the established practices of another entity.
-
E.
medicalPractice
Indicates a relationship where an entity engages in or carries out the professional provision of medical care or services.
- F. None of above. chosen
Provenance (4 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_69d806a9fe888190b081e2d9ea665d6c |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d981b27a8c81909a92ab7be5d3a7e9 |
completed | April 10, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69d98043a74c81908648e6cd0b4c7f71 |
completed | April 10, 2026, 10:57 p.m. |
| PDg | Predicate description generation | batch_69d98134df64819084a5674f9475dcc2 |
completed | April 10, 2026, 11:01 p.m. |
Created at: April 9, 2026, 9:08 p.m.