Triple
T9766444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Konstanz |
E237005
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Kreuzlingen |
E305911
|
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: Kreuzlingen | Statement: [Konstanz, adjacentTo, Kreuzlingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kreuzlingen Context triple: [Konstanz, adjacentTo, Kreuzlingen]
-
A.
Kreuzlingen
chosen
Kreuzlingen is a Swiss town in the canton of Thurgau, located on the southern shore of Lake Constance near the German border.
-
B.
Sulzach
Sulzach is a small river in Bavaria, Germany, that flows through the town of Feuchtwangen and forms part of the local Franconian river system.
-
C.
Ruhpolding
Ruhpolding is a Bavarian alpine town in southeastern Germany known for its winter sports facilities, especially biathlon, and its scenic location in the Chiemgau Alps.
-
D.
Nesslau-Krummenau
Nesslau-Krummenau was a former municipality in the canton of St. Gallen in northeastern Switzerland, known for its rural Alpine setting and merger into the larger municipality of Nesslau.
-
E.
Küsnacht
Küsnacht is a picturesque Swiss municipality on the shores of Lake Zurich, known for its affluent residential character and scenic lakeside setting.
- 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_69ca84d831b8819090322686b47887ce |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda0a15e408190909745cb1c30937d |
completed | April 1, 2026, 10:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1e4064c8c8190b18f419135f049a9 |
completed | April 5, 2026, 4:24 a.m. |
Created at: March 30, 2026, 8:25 p.m.