Triple
T755068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University Hospital Zurich |
E15535
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
USZ
USZ is a major public teaching hospital in Zurich, Switzerland, affiliated with the University of Zurich and known for its advanced medical care and research.
|
E88690
|
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: USZ | Statement: [University Hospital Zurich, shortName, USZ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: USZ Context triple: [University Hospital Zurich, shortName, USZ]
-
A.
USAR
USAR is the commonly used abbreviation for the United States Army Reserve, the federal reserve force of the U.S. Army composed of part-time soldiers who support active-duty operations.
-
B.
UA
UA is the two-letter IATA airline designator used worldwide to identify United Airlines on tickets, schedules, and flight information.
-
C.
UA
UA is a major public research university located in Tuscaloosa, Alabama, known for its strong academic programs and prominent Crimson Tide athletics.
-
D.
UA
UA is the two-letter ISO 3166-1 alpha-2 country code assigned to Ukraine for international standardization and identification purposes.
-
E.
UL
UL is the vehicle registration code used on license plates for the city of Ulm in Germany.
- 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: USZ Triple: [University Hospital Zurich, shortName, USZ]
Generated description
USZ is a major public teaching hospital in Zurich, Switzerland, affiliated with the University of Zurich and known for its advanced medical care and research.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: USZ Target entity description: USZ is a major public teaching hospital in Zurich, Switzerland, affiliated with the University of Zurich and known for its advanced medical care and research.
-
A.
USAR
USAR is the commonly used abbreviation for the United States Army Reserve, the federal reserve force of the U.S. Army composed of part-time soldiers who support active-duty operations.
-
B.
UA
UA is the two-letter IATA airline designator used worldwide to identify United Airlines on tickets, schedules, and flight information.
-
C.
UA
UA is a major public research university located in Tuscaloosa, Alabama, known for its strong academic programs and prominent Crimson Tide athletics.
-
D.
UA
UA is the two-letter ISO 3166-1 alpha-2 country code assigned to Ukraine for international standardization and identification purposes.
-
E.
UL
UL is the vehicle registration code used on license plates for the city of Ulm in Germany.
- 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_69a493599a0081908da65f3407af1ef2 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a66820548190b373deb117187c2c |
completed | March 1, 2026, 8:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a654eae9608190af3b410ecc041660 |
completed | March 3, 2026, 3:26 a.m. |
| NEDg | Description generation | batch_69a65555e7748190b2a55548e4058bc1 |
completed | March 3, 2026, 3:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a656d5f28481908ff3fd5fb71b1440 |
completed | March 3, 2026, 3:34 a.m. |
Created at: March 1, 2026, 7:37 p.m.