Triple
T10029252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nassau-Idstein line |
E204810
|
entity |
| Predicate | hasCapital |
P204
|
FINISHED |
| Object | Idstein |
E224946
|
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: Idstein | Statement: [Nassau-Idstein line, hasCapital, Idstein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Idstein Context triple: [Nassau-Idstein line, hasCapital, Idstein]
-
A.
Idstein
chosen
Idstein is a historic town in the German state of Hesse, known for its well-preserved medieval old town and timber-framed architecture.
-
B.
Dornstadt
Dornstadt is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, located near the city of Ulm.
-
C.
Drensteinfurt
Drensteinfurt is a small town in North Rhine-Westphalia, Germany, known for its historic architecture and location in the Münsterland region.
-
D.
Starnberg
Starnberg is a lakeside town in Bavaria, Germany, known for its affluent residential character and scenic location on Lake Starnberg southwest of Munich.
-
E.
Riedering
Riedering is a municipality in Bavaria, Germany, situated in the Alpine foothills near the city of Rosenheim.
- 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_69ca834d77188190ad645e33e8ca3200 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdcde69bd08190a5c79ec8487dfff6 |
completed | April 2, 2026, 2:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d30020305c81909c4fb01291c70cb6 |
completed | April 6, 2026, 12:36 a.m. |
Created at: March 30, 2026, 8:54 p.m.