Triple
T23221548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xinjiang Medical University |
E580905
|
entity |
| Predicate | hasAffiliatedHospital |
P20607
|
FINISHED |
| Object |
Affiliated Traditional Chinese Medicine Hospital of Xinjiang Medical University
The Affiliated Traditional Chinese Medicine Hospital of Xinjiang Medical University is a major teaching and clinical center in Xinjiang that specializes in traditional Chinese medicine while integrating modern medical practices.
|
E1581069
|
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: Affiliated Traditional Chinese Medicine Hospital of Xinjiang Medical University | Statement: [Xinjiang Medical University, hasAffiliatedHospital, Affiliated Traditional Chinese Medicine Hospital of Xinjiang Medical University]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Affiliated Traditional Chinese Medicine Hospital of Xinjiang Medical University Context triple: [Xinjiang Medical University, hasAffiliatedHospital, Affiliated Traditional Chinese Medicine Hospital of Xinjiang Medical University]
-
A.
Second Affiliated Hospital of Xinjiang Medical University
The Second Affiliated Hospital of Xinjiang Medical University is a major teaching and comprehensive medical center in Xinjiang, China, providing clinical care, medical education, and research under the university’s supervision.
-
B.
First Affiliated Hospital of Xinjiang Medical University
The First Affiliated Hospital of Xinjiang Medical University is a major teaching and tertiary care hospital in Xinjiang, China, providing clinical services, medical education, and research.
-
C.
Xinjiang Medical University
Xinjiang Medical University is a major medical higher education and research institution in China’s Xinjiang Uyghur Autonomous Region.
-
D.
Xiehe Hospital
Xiehe Hospital is a leading tertiary teaching hospital in Beijing renowned for its high-quality medical care, research, and affiliation with Peking Union Medical College.
-
E.
The First Affiliated Hospital, Zhejiang University School of Medicine
The First Affiliated Hospital, Zhejiang University School of Medicine is a major teaching and tertiary care hospital in Hangzhou, China, renowned for its advanced medical services, research, and clinical education.
- 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: Affiliated Traditional Chinese Medicine Hospital of Xinjiang Medical University Triple: [Xinjiang Medical University, hasAffiliatedHospital, Affiliated Traditional Chinese Medicine Hospital of Xinjiang Medical University]
Generated description
The Affiliated Traditional Chinese Medicine Hospital of Xinjiang Medical University is a major teaching and clinical center in Xinjiang that specializes in traditional Chinese medicine while integrating modern medical practices.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Affiliated Traditional Chinese Medicine Hospital of Xinjiang Medical University Target entity description: The Affiliated Traditional Chinese Medicine Hospital of Xinjiang Medical University is a major teaching and clinical center in Xinjiang that specializes in traditional Chinese medicine while integrating modern medical practices.
-
A.
Second Affiliated Hospital of Xinjiang Medical University
The Second Affiliated Hospital of Xinjiang Medical University is a major teaching and comprehensive medical center in Xinjiang, China, providing clinical care, medical education, and research under the university’s supervision.
-
B.
First Affiliated Hospital of Xinjiang Medical University
The First Affiliated Hospital of Xinjiang Medical University is a major teaching and tertiary care hospital in Xinjiang, China, providing clinical services, medical education, and research.
-
C.
Xinjiang Medical University
Xinjiang Medical University is a major medical higher education and research institution in China’s Xinjiang Uyghur Autonomous Region.
-
D.
Xiehe Hospital
Xiehe Hospital is a leading tertiary teaching hospital in Beijing renowned for its high-quality medical care, research, and affiliation with Peking Union Medical College.
-
E.
The First Affiliated Hospital, Zhejiang University School of Medicine
The First Affiliated Hospital, Zhejiang University School of Medicine is a major teaching and tertiary care hospital in Hangzhou, China, renowned for its advanced medical services, research, and clinical education.
- F. None of above. chosen
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_69e2460389408190be74f41d217799a9 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1922924308190a26b00e09ce60ecd |
completed | April 29, 2026, 5:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c4c79c6788190bd66f55a9e0560ca |
completed | May 19, 2026, 11:41 a.m. |
| NEDg | Description generation | batch_6a0c50930c348190b81f1a4cbf432d93 |
completed | May 19, 2026, 11:59 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c511e9be4819083eb3ec76fea8d51 |
completed | May 19, 2026, 12:01 p.m. |
Created at: April 17, 2026, 4:08 p.m.