Triple
T13131598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Canon of Medicine |
E311976
|
entity |
| Predicate | book5Covers |
P97684
|
FINISHED |
| Object | compound drugs and pharmacology |
—
|
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: compound drugs and pharmacology | Statement: [The Canon of Medicine, book5Covers, compound drugs and pharmacology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: book5Covers Context triple: [The Canon of Medicine, book5Covers, compound drugs and pharmacology]
-
A.
book5Content
Indicates that one entity is the content or textual material contained within the book represented by the other entity.
-
B.
book5Title
Indicates the title assigned to the book identified as "book5."
-
C.
book1Contains
Indicates that one book includes, encloses, or has as part of its content another specified element or section.
-
D.
containsBook
Indicates that one entity (typically a container or collection) includes a specific book as part of its contents.
-
E.
book5Subject
chosen
Indicates that an entity serves as the subject (main topic or focus) of the fifth book in a series or collection.
- 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_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. |
Created at: April 9, 2026, 9:08 p.m.