Triple
T9540536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Landshut (district) |
E230144
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Vilsbiburg |
E230142
|
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: Vilsbiburg | Statement: [Landshut (district), contains, Vilsbiburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vilsbiburg Context triple: [Landshut (district), contains, Vilsbiburg]
-
A.
Vilsbiburg
chosen
Vilsbiburg is a small town in southeastern Germany known for its historic Bavarian character and location within the region of Lower Bavaria.
-
B.
Bergneustadt
Bergneustadt is a small town in North Rhine-Westphalia, Germany, known for its location in the hilly Oberbergischer Kreis region and its traditional half-timbered architecture.
-
C.
Ortenburg
Ortenburg is a market town in Lower Bavaria, Germany, known for its historic castle and role as a former seat of the Counts of Ortenburg.
-
D.
Arensburg
Arensburg is the former German name for Kuressaare, a historic town and seaside resort on Saaremaa Island in Estonia.
-
E.
Drensteinfurt
Drensteinfurt is a small town in North Rhine-Westphalia, Germany, known for its historic architecture and location in the Münsterland region.
- 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_69ca847b1b3081908f72bc932c17cc41 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98e695948190ab107fff38c57de7 |
completed | April 1, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d14c5da5a081909d646c69d5de8e18 |
completed | April 4, 2026, 5:37 p.m. |
Created at: March 30, 2026, 8:01 p.m.