Triple
T16886370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Igersheim |
E421550
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object | MGH |
E413669
|
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: MGH | Statement: [Igersheim, vehicleRegistrationCode, MGH]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MGH Context triple: [Igersheim, vehicleRegistrationCode, MGH]
-
A.
MGH
chosen
MGH is the vehicle registration code for the town of Bad Mergentheim in the German state of Baden-Württemberg.
-
B.
MGH
MGH is the commonly used abbreviation for Michael Garron Hospital, a community teaching hospital in Toronto, Canada.
-
C.
Mass General Brigham
Mass General Brigham is a large, Boston-based nonprofit healthcare system and academic medical network that includes Massachusetts General Hospital and Brigham and Women’s Hospital among its flagship institutions.
-
D.
Boston Medical Center
Boston Medical Center is a major academic medical center and safety-net hospital in Boston known for providing comprehensive care and serving a large underserved population.
-
E.
Massachusetts General Hospital
Massachusetts General Hospital is a major Boston-based teaching hospital and biomedical research center widely recognized for its clinical excellence and affiliation with Harvard Medical School.
- 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_69d889d470fc8190b4aec199636c0c56 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3bbc126e881909dae8133ad34acc9 |
completed | April 18, 2026, 5:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00c2bcf290819098be9def471e02b8 |
completed | May 10, 2026, 5:39 p.m. |
Created at: April 10, 2026, 5:29 a.m.