Triple
T21205850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ankum |
E522576
|
entity |
| Predicate | hasNeighbouringMunicipality |
P224
|
FINISHED |
| Object | Alfhausen |
—
|
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: Alfhausen | Statement: [Ankum, hasNeighbouringMunicipality, Alfhausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alfhausen Context triple: [Ankum, hasNeighbouringMunicipality, Alfhausen]
-
A.
Alfhausen
chosen
Alfhausen is a small municipality in Lower Saxony, Germany, known for its rural character and location within the Osnabrück region.
-
B.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
C.
Altshausen
Altshausen is a small historic town in the German state of Baden-Württemberg, known for its former ducal residence and picturesque setting in Upper Swabia.
-
D.
Aidhausen
Aidhausen is a small municipality in the Lower Franconia region of Bavaria, Germany.
-
E.
Nattenhausen
Nattenhausen is a small village in the Bavarian district of Günzburg in southern Germany.
- 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_69e0b5112d8881909510b2dcdc93106d |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e734342e9081909e241bed54dbc0b4 |
completed | April 21, 2026, 8:24 a.m. |
Created at: April 16, 2026, 3:20 p.m.