Triple
T1085448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Department of Internal Medicine, Cairo University |
E24039
|
entity |
| Predicate | hasSubspecialty |
P5461
|
FINISHED |
| Object | cardiology |
—
|
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: cardiology | Statement: [Department of Internal Medicine, Cairo University, hasSubspecialty, cardiology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubspecialty Context triple: [Department of Internal Medicine, Cairo University, hasSubspecialty, cardiology]
-
A.
hasSpecialty
Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
-
B.
hasSubdiscipline
chosen
Indicates that one discipline includes another, more specialized field of study as a subordinate branch.
-
C.
subDisciplineOf
Indicates that one discipline is a more specialized or narrower field within another, broader discipline.
-
D.
hasSubConcept
Indicates that one concept is a more specific, subordinate, or narrower idea within the scope of another, more general concept.
-
E.
hasSpecialProcedure
Indicates that a particular entity is associated with or governed by a designated special procedure or process.
- 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_69a49404428c819092dcc9632f5f7b8b |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b961d0cc8190858296b44fab2f32 |
completed | March 1, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69a4b7407914819092ed933a7316b450 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.