Triple
T22155037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dalfsen |
E547512
|
entity |
| Predicate | neighboringMunicipality |
P17964
|
FINISHED |
| Object | Hardenberg |
—
|
NE NERFINISHED |
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: Hardenberg | Statement: [Dalfsen, neighboringMunicipality, Hardenberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hardenberg Context triple: [Dalfsen, neighboringMunicipality, Hardenberg]
-
A.
Hardenberg
chosen
Hardenberg is a municipality in the Dutch province of Overijssel, known for its rural landscapes, small towns, and location near the German border.
-
B.
Udenhausen
Udenhausen is a district of the town of Boppard in the Rhineland-Palatinate region of western Germany.
-
C.
Fahrenkopf
Fahrenkopf is a surname most prominently associated with Frank J. Fahrenkopf Jr., an American lawyer, lobbyist, and former chairman of the Republican National Committee.
-
D.
Hüttenberg
Hüttenberg is a municipality in the central German state of Hesse, known for its rural character and proximity to the city of Wetzlar.
-
E.
Kaltenborn
Kaltenborn is a small municipality in the Ahrweiler district of Rhineland-Palatinate, western Germany, situated in the Eifel region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e3b52088190ad5df386d01eb2fb |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129f7d034819092ecf9682e549c9a |
completed | April 28, 2026, 9:43 p.m. |
Created at: April 16, 2026, 8:33 p.m.