Triple
T9146306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Starnberg |
E219462
|
entity |
| Predicate | hasLakesideTown |
P59883
|
FINISHED |
| Object | Seeshaupt |
E215210
|
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: Seeshaupt | Statement: [Lake Starnberg, hasLakesideTown, Seeshaupt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seeshaupt Context triple: [Lake Starnberg, hasLakesideTown, Seeshaupt]
-
A.
Seeshaupt
chosen
Seeshaupt is a Bavarian municipality and lakeside village known for its scenic location at the southern end of Lake Starnberg in southern Germany.
-
B.
Freyung
Freyung is a small town in southeastern Bavaria, Germany, known as a gateway to the Bavarian Forest region.
-
C.
Obergartzem
Obergartzem is a village in the town of Mechernich in North Rhine-Westphalia, western Germany.
-
D.
Seckbach
Seckbach is a district in the east of Frankfurt am Main, Germany, known for its residential character and proximity to green spaces like the Lohrberg.
-
E.
Seelenberg
Seelenberg is a small village that forms one of the local subdivisions of the municipality of Schmitten 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_69ca83e121dc81909912bd66953081c5 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca917914c8190b97ca9169bbd1e5e |
completed | April 1, 2026, 5:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0482995cc81909bfc202cbab7f8a1 |
completed | April 3, 2026, 11:07 p.m. |
Created at: March 30, 2026, 7:20 p.m.