Triple
T755097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University Hospital Zurich |
E15535
|
entity |
| Predicate | offersFellowshipPrograms |
P19241
|
FINISHED |
| Object | true |
—
|
LITERAL 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: true | Statement: [University Hospital Zurich, offersFellowshipPrograms, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersFellowshipPrograms Context triple: [University Hospital Zurich, offersFellowshipPrograms, true]
-
A.
offersInternationalPrograms
Indicates that an institution or organization provides programs or courses available to participants from other countries or across national borders.
-
B.
offersProgramsIn
Indicates that an institution or provider makes educational or training programs available in a particular field, subject, or area.
-
C.
offersProgramLevel
Indicates that an entity provides or makes available an academic or training program at a specified level (e.g., undergraduate, graduate, certificate).
-
D.
hasScholarships
Indicates that an entity provides, offers, or is associated with one or more scholarships to another entity.
-
E.
offersProgram
Indicates that an entity provides or makes available a specific program (such as a course, curriculum, or initiative).
- F. None of above. chosen
Provenance (4 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. |
| PD | Predicate disambiguation | batch_69a4a50348088190873a1446db657a78 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a62b497081909503c8d30c7ce1db |
completed | March 1, 2026, 8:48 p.m. |
Created at: March 1, 2026, 7:37 p.m.