Triple
T32340261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Medicine, Masaryk University |
E826291
|
entity |
| Predicate | affiliatedWith |
P254
|
FINISHED |
| Object |
University Hospital Brno
University Hospital Brno is a major teaching and research hospital in Brno, Czech Republic, serving as a key clinical center for medical education and specialized healthcare.
|
E2002811
|
NE 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: University Hospital Brno | Statement: [Faculty of Medicine, Masaryk University, affiliatedWith, University Hospital Brno]
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: University Hospital Brno Triple: [Faculty of Medicine, Masaryk University, affiliatedWith, University Hospital Brno]
Generated description
University Hospital Brno is a major teaching and research hospital in Brno, Czech Republic, serving as a key clinical center for medical education and specialized healthcare.
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_69f34913d9048190befaa634025232be |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6be20cd6c8190b365c130d0a286e7 |
completed | May 3, 2026, 3:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a30572a7b1881909db65da279fed378 |
completed | June 15, 2026, 7:48 p.m. |
| NEDg | Description generation | batch_6a31af7af8a081908c3c49e456470e61 |
completed | June 16, 2026, 8:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a31bae5e0388190a4d8a985ba179c93 |
completed | June 16, 2026, 9:06 p.m. |
Created at: May 1, 2026, 12:48 a.m.