Triple
T22497156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wolfgang Mommsen |
E556170
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Marburg |
—
|
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: Marburg | Statement: [Wolfgang Mommsen, placeOfBirth, Marburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marburg Context triple: [Wolfgang Mommsen, placeOfBirth, Marburg]
-
A.
Marburg
chosen
Marburg is a historic university town in central Germany known for its well-preserved medieval old town and the Philipps-Universität, one of the oldest Protestant universities in the world.
-
B.
Marburg
Marburg is a small rural township in Queensland, Australia, known for its historic buildings and location between Ipswich and Toowoomba.
-
C.
Diemelstadt
Diemelstadt is a small town in the German state of North Rhine-Westphalia, known for its rural character and location near the Diemel River.
-
D.
Vienenburg
Vienenburg is a district of Goslar in Lower Saxony, Germany, known for its historic town center and proximity to the Harz Mountains.
-
E.
Neustadt Warburg
Neustadt Warburg is a district or quarter of the German town of Warburg in North Rhine-Westphalia.
- 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_69e11e5445bc8190b6a9481926db3355 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15cb31b8081909553fa860a07e746 |
completed | April 29, 2026, 1:19 a.m. |
Created at: April 16, 2026, 8:50 p.m.