Triple
T17130832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hadassah Ein Kerem Medical Center |
E415716
|
entity |
| Predicate | affiliatedWith |
P254
|
FINISHED |
| Object |
Hebrew University Faculty of Medicine
The Hebrew University Faculty of Medicine is a leading Israeli medical school and research institution based in Jerusalem, known for training physicians and advancing biomedical research in collaboration with major teaching hospitals.
|
E415716
|
NE FINISHED |
How this triple was built (4 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: Hebrew University Faculty of Medicine | Statement: [Hadassah Ein Kerem Medical Center, affiliatedWith, Hebrew University Faculty of Medicine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hebrew University Faculty of Medicine Context triple: [Hadassah Ein Kerem Medical Center, affiliatedWith, Hebrew University Faculty of Medicine]
-
A.
Sackler Faculty of Medicine
The Sackler Faculty of Medicine is the medical school of Tel Aviv University, known for training physicians and conducting biomedical research in Israel.
-
B.
Rappaport Faculty of Medicine
The Rappaport Faculty of Medicine is the medical school of the Technion – Israel Institute of Technology in Haifa, known for its research excellence and association with Nobel laureate Aaron Ciechanover.
-
C.
Hadassah Ein Kerem Medical Center
Hadassah Ein Kerem Medical Center is a major university hospital and teaching facility of the Hebrew University in Jerusalem, renowned for its advanced medical services and research.
-
D.
Sheba Medical Center
Sheba Medical Center is Israel’s largest and one of the Middle East’s leading hospitals, renowned for its advanced medical research, comprehensive clinical care, and innovation in healthcare.
-
E.
Meir Medical Center
Meir Medical Center is a major public hospital in Israel known for providing comprehensive medical services and serving as a teaching and research institution.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Hebrew University Faculty of Medicine Triple: [Hadassah Ein Kerem Medical Center, affiliatedWith, Hebrew University Faculty of Medicine]
Generated description
The Hebrew University Faculty of Medicine is a leading Israeli medical school and research institution based in Jerusalem, known for training physicians and advancing biomedical research in collaboration with major teaching hospitals.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hebrew University Faculty of Medicine Target entity description: The Hebrew University Faculty of Medicine is a leading Israeli medical school and research institution based in Jerusalem, known for training physicians and advancing biomedical research in collaboration with major teaching hospitals.
-
A.
Sackler Faculty of Medicine
The Sackler Faculty of Medicine is the medical school of Tel Aviv University, known for training physicians and conducting biomedical research in Israel.
-
B.
Rappaport Faculty of Medicine
The Rappaport Faculty of Medicine is the medical school of the Technion – Israel Institute of Technology in Haifa, known for its research excellence and association with Nobel laureate Aaron Ciechanover.
-
C.
Hadassah Ein Kerem Medical Center
chosen
Hadassah Ein Kerem Medical Center is a major university hospital and teaching facility of the Hebrew University in Jerusalem, renowned for its advanced medical services and research.
-
D.
Sheba Medical Center
Sheba Medical Center is Israel’s largest and one of the Middle East’s leading hospitals, renowned for its advanced medical research, comprehensive clinical care, and innovation in healthcare.
-
E.
Meir Medical Center
Meir Medical Center is a major public hospital in Israel known for providing comprehensive medical services and serving as a teaching and research institution.
- F. None of above.
Provenance (5 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_69d886d15af4819092f92f8a129763e6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f029d1a48190a9d4094827d11d23 |
completed | April 18, 2026, 8:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01414cd5d481908d11eb230d2283cd |
completed | May 11, 2026, 2:39 a.m. |
| NEDg | Description generation | batch_6a01422c0f088190b162c7086bc93585 |
completed | May 11, 2026, 2:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0142f274ec819081eb15a3ea0e1b13 |
completed | May 11, 2026, 2:46 a.m. |
Created at: April 10, 2026, 5:36 a.m.