Triple
T13453666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johann Bugenhagen |
E311173
|
entity |
| Predicate | workLocation |
P7
|
FINISHED |
| Object | Brunswick |
E41721
|
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: Brunswick | Statement: [Johann Bugenhagen, workLocation, Brunswick]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brunswick Context triple: [Johann Bugenhagen, workLocation, Brunswick]
-
A.
Brunswick
Brunswick is a football club that competes in the Netherlands' second-tier league system.
-
B.
Brunswick
Brunswick is a suburban city in northeastern Ohio, United States, located in Medina County within the Greater Cleveland metropolitan area.
-
C.
Brunswick
chosen
Brunswick is a historic city in northern Germany known for its medieval heritage and as the birthplace of mathematician Carl Friedrich Gauss.
-
D.
Brunswick
Brunswick is a coastal town in Maine known for its historic charm, cultural amenities, and role as the home of Bowdoin College.
-
E.
Brunswick
Brunswick is a coastal city in southeastern Georgia known for its historic port, maritime industry, and proximity to the Golden Isles.
- 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_69d806a938b8819097ec43a2229fc7f9 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaefae85481909e6a59797cbb25e7 |
completed | April 12, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7399e33008190b10c14f30ff0c0d2 |
completed | May 3, 2026, 12:03 p.m. |
Created at: April 9, 2026, 9:41 p.m.