Triple
T16214530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karow |
E393550
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Französisch Buchholz |
E393551
|
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: Französisch Buchholz | Statement: [Karow, adjacentTo, Französisch Buchholz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Französisch Buchholz Context triple: [Karow, adjacentTo, Französisch Buchholz]
-
A.
Französisch Buchholz
chosen
Französisch Buchholz is a northeastern locality of Berlin known for its village-like character and incorporation into the borough of Pankow.
-
B.
Riedholz
Riedholz is a small Swiss municipality located in the canton of Solothurn.
-
C.
Kestenholz
Kestenholz is a municipality in the canton of Solothurn in Switzerland, located in the Gäu district.
-
D.
Plauen
Plauen is a historic town in eastern Germany known for its textile industry and intricate lace production.
-
E.
Bramsche
Bramsche is a town in Lower Saxony, Germany, known for its location near Osnabrück and its historical textile industry.
- 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_69d87f1f5bd08190bd01cac0d5b9d2ef |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e227f393e08190be93400d754f0a2d |
completed | April 17, 2026, 12:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000794e6c881909c4521e4dd031971 |
completed | May 10, 2026, 4:20 a.m. |
Created at: April 10, 2026, 5:03 a.m.