Triple
T18621704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sangerhausen |
E455166
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object | MSH |
—
|
NE NERFINISHED |
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: MSH | Statement: [Sangerhausen, vehicleRegistrationCode, MSH]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MSH Context triple: [Sangerhausen, vehicleRegistrationCode, MSH]
-
A.
MSH
chosen
MSH is the vehicle registration code for the Mansfeld-Südharz district in the German state of Saxony-Anhalt.
-
B.
MSHSL
MSHSL is the governing body that oversees and regulates high school sports and fine arts activities for member schools in Minnesota.
-
C.
MHS
MHS is the acronym for the U.S. Military Health System, the organization that provides healthcare services to active-duty service members, retirees, and their families.
-
D.
MHS
MHS is the National Rail station code for Meadowhall railway station in Sheffield, South Yorkshire, England.
-
E.
MSA
MSA is the standardized, literary form of Arabic used in formal writing, media, education, and official communication across the Arab world.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d38cc7948190a55ea64e5638994e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54f0146f48190a872032db6e660c6 |
completed | April 19, 2026, 9:54 p.m. |
Created at: April 10, 2026, 11:46 a.m.