Triple
T11272913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nonnenwerth |
E266856
|
entity |
| Predicate | nearSettlement |
P3883
|
FINISHED |
| Object | Rolandseck |
E188136
|
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: Rolandseck | Statement: [Nonnenwerth, nearSettlement, Rolandseck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rolandseck Context triple: [Nonnenwerth, nearSettlement, Rolandseck]
-
A.
Rolandseck
chosen
Rolandseck is a district of Remagen in Rhineland-Palatinate, Germany, known for its scenic location on the Rhine and its historic railway station and cultural venues.
-
B.
Beutelsbach
Beutelsbach is a small municipality in the rural Passau district of Lower Bavaria in southeastern Germany.
-
C.
Haguenau
Haguenau is a historic town in northeastern France’s Alsace region, known for its medieval heritage, cultural traditions, and role as a local economic center.
-
D.
Niederlahnstein
Niederlahnstein is a former town on the right bank of the Rhine in Rhineland-Palatinate, Germany, now part of the city of Lahnstein.
-
E.
Willanzheim
Willanzheim is a small municipality in the Kitzingen district of Bavaria, Germany, known for its rural character and Franconian wine-growing tradition.
- 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_69d6aac8c2f48190ad0596f1f89f0470 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e965c9048190804ebb48f0a4817b |
completed | April 9, 2026, 6:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5b7b051988190abec04740df75c89 |
completed | April 20, 2026, 5:20 a.m. |
Created at: April 8, 2026, 9:31 p.m.