Triple
T3727523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avicenna |
E81784
|
entity |
| Predicate | workCharacterization |
P44666
|
FINISHED |
| Object | The Canon of Medicine served as a standard medical text in Europe and the Islamic world for centuries |
E311976
|
NE FINISHED |
How this triple was built (3 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: The Canon of Medicine served as a standard medical text in Europe and the Islamic world for centuries | Statement: [Avicenna, workCharacterization, The Canon of Medicine served as a standard medical text in Europe and the Islamic world for centuries]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Canon of Medicine served as a standard medical text in Europe and the Islamic world for centuries Context triple: [Avicenna, workCharacterization, The Canon of Medicine served as a standard medical text in Europe and the Islamic world for centuries]
-
A.
The Canon of Medicine
chosen
The Canon of Medicine is a seminal 11th-century medical encyclopedia by Avicenna that systematized Greco-Arabic medical knowledge and served as a standard medical text in both the Islamic world and Europe for centuries.
-
B.
Syriac medical tradition
The Syriac medical tradition was a late antique and early medieval body of medical knowledge, largely transmitted in the Syriac language, that preserved and adapted Greco-Roman medicine and served as a crucial conduit to later Islamic medical scholarship.
-
C.
Persian medicine
Persian medicine is a traditional medical system that developed in the Persian cultural sphere, integrating ancient Greek, Indian, and local practices into a comprehensive theory of health, disease, and treatment.
-
D.
Kitab al-Tibb al-Nabawi (Prophetic medicine works)
Kitab al-Tibb al-Nabawi refers to classical Islamic treatises that compile and explain the health-related sayings and practices attributed to the Prophet Muhammad, blending religious guidance with medical knowledge.
-
E.
Galenic medicine
Galenic medicine is an ancient medical system based on the theories of the Greek physician Galen, emphasizing humoral balance and systematic clinical observation, which profoundly shaped later medical traditions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workCharacterization Context triple: [Avicenna, workCharacterization, The Canon of Medicine served as a standard medical text in Europe and the Islamic world for centuries]
-
A.
workCharacterType
Indicates that a work involves or features a character of a specified type or role.
-
B.
workDescribedIn
Indicates that a work (such as a publication or document) provides a description or account of the referenced entity.
-
C.
ruleCharacterization
Indicates that one rule is described, defined, or characterized in terms of another rule or set of rules.
-
D.
workDescribedAs
chosen
Indicates that one entity’s work, project, or output is characterized, labeled, or referred to by a particular description, title, or phrase.
-
E.
workBasedOnThisCharacter
Indicates that a creative work is based on, inspired by, or derived from the referenced character.
- F. None of above.
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_69ad8b1b7ef081908d2d381bbf54985a |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcaf7a6908190bd0c3bb5c55ab9ee |
completed | March 8, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4db1102a08190b5965c474dfab6db |
completed | March 14, 2026, 3:50 a.m. |
| PD | Predicate disambiguation | batch_69adc0452f5081909c79e114a86cce8c |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:34 p.m.