Triple
T34006923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Medicine, University of Murcia |
E871990
|
entity |
| Predicate | affiliatedWith |
P254
|
FINISHED |
| Object |
University of Murcia Teaching Hospitals
University of Murcia Teaching Hospitals is the clinical and research hospital network that serves as the primary teaching and training setting for the University of Murcia’s medical and health sciences programs.
|
E2076993
|
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 of Murcia Teaching Hospitals | Statement: [Faculty of Medicine, University of Murcia, affiliatedWith, University of Murcia Teaching Hospitals]
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 of Murcia Teaching Hospitals Triple: [Faculty of Medicine, University of Murcia, affiliatedWith, University of Murcia Teaching Hospitals]
Generated description
University of Murcia Teaching Hospitals is the clinical and research hospital network that serves as the primary teaching and training setting for the University of Murcia’s medical and health sciences programs.
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_69f349a08848819084b348d64c1879c3 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f70ac7335881909e9125c0de0efa1e |
completed | May 3, 2026, 8:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3692eb3d648190a0666d92fdd68619 |
completed | June 20, 2026, 1:17 p.m. |
| NEDg | Description generation | batch_6a369360e05c81908b5104d9516b2bb1 |
completed | June 20, 2026, 1:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a369446643c8190b9308ded820afd07 |
completed | June 20, 2026, 1:23 p.m. |
Created at: May 1, 2026, 1:50 a.m.