Triple
T8810240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tutzing |
E209639
|
entity |
| Predicate | nearbyTown |
P3883
|
FINISHED |
| Object | Starnberg |
E42787
|
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: Starnberg | Statement: [Tutzing, nearbyTown, Starnberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Starnberg Context triple: [Tutzing, nearbyTown, Starnberg]
-
A.
Starnberg
chosen
Starnberg is a lakeside town in Bavaria, Germany, known for its affluent residential character and scenic location on Lake Starnberg southwest of Munich.
-
B.
Landsberg
Landsberg is a town in the Saalekreis district of the German state of Saxony-Anhalt.
-
C.
Dornstadt
Dornstadt is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, located near the city of Ulm.
-
D.
Idstein
Idstein is a historic town in the German state of Hesse, known for its well-preserved medieval old town and timber-framed architecture.
-
E.
Brackenheim
Brackenheim is a small town in the German state of Baden-Württemberg, best known as the birthplace of Theodor Heuss, the first President of the Federal Republic of 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_69ca8363f3308190a47e3f1ebd51f613 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5fd69df4819091e9a7dad87265a4 |
completed | March 31, 2026, 11:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d017060fd08190bd053f988bd74048 |
completed | April 3, 2026, 7:37 p.m. |
Created at: March 30, 2026, 6:45 p.m.