Triple
T13131597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Canon of Medicine |
E311976
|
entity |
| Predicate | book4Covers |
P108230
|
FINISHED |
| Object | general diseases and systemic conditions |
—
|
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: general diseases and systemic conditions | Statement: [The Canon of Medicine, book4Covers, general diseases and systemic conditions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: book4Covers Context triple: [The Canon of Medicine, book4Covers, general diseases and systemic conditions]
-
A.
earliestBooksCover
Indicates that the cover image or design is taken from the earliest edition(s) of the referenced books.
-
B.
cover
Indicates that one entity extends over, conceals, protects, or provides a surface or layer for another entity.
-
C.
isCoverOf
Indicates that one entity functions as a protective or enclosing layer placed over another entity.
-
D.
notableCover
Indicates that one entity is a particularly well-known or significant cover version or adaptation of another entity.
-
E.
titleIVCovers
Indicates that the subject entity falls under or is included within the scope of Title IV regulations or provisions.
- 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.