Triple
T9364417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | district of Pfaffenhofen an der Ilm |
E225363
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Geisenfeld |
E481806
|
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: Geisenfeld | Statement: [district of Pfaffenhofen an der Ilm, hasMunicipality, Geisenfeld]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Geisenfeld Context triple: [district of Pfaffenhofen an der Ilm, hasMunicipality, Geisenfeld]
-
A.
Geisenfeld
chosen
Geisenfeld is a small town in Bavaria, Germany, known as the birthplace of prominent early Nazi politician Gregor Strasser.
-
B.
Ochsenfeld
Ochsenfeld is a German surname most notably borne by physicist Robert Ochsenfeld, known for his work on superconductivity.
-
C.
Dornstadt
Dornstadt is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, located near the city of Ulm.
-
D.
Pottendorf
Pottendorf is a market town in Lower Austria known for its historic castle and location within the Baden district.
-
E.
Pennenfeld
Pennenfeld is a residential subdistrict of the Bonn borough of Bad Godesberg in Germany.
- 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_69ca842bdd648190904131d58620d448 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd503fd7f081909655e2a880c84834 |
completed | April 1, 2026, 5:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d74fa545b8819092809c605542476a |
completed | April 9, 2026, 7:05 a.m. |
Created at: March 30, 2026, 7:42 p.m.