Triple
T17039924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. George's University |
E413417
|
entity |
| Predicate | grantsDegree |
P49
|
FINISHED |
| Object | MD |
E450854
|
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: MD | Statement: [St. George's University, grantsDegree, MD]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MD Context triple: [St. George's University, grantsDegree, MD]
-
A.
MD
MD is the station code used to identify Maitland railway station in New South Wales, Australia.
-
B.
MD
MD is the official two-letter United States Postal Service abbreviation used to designate the state of Maryland.
-
C.
MD
chosen
MD is a postgraduate medical degree focused on advanced clinical training and specialization for physicians.
-
D.
MD
MD is the vehicle registration code used on license plates for the Austrian district of Mödling.
-
E.
MA
MA is the vehicle registration code used on license plates for the German city of Mannheim.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d886cd18288190b006abab23f811b7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d8f5844c819097eade4a2b42ab91 |
completed | April 18, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a011b5ceb048190a7f6cf2361360f90 |
completed | May 10, 2026, 11:57 p.m. |
Created at: April 10, 2026, 5:33 a.m.