Triple
T12566998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Westphalia |
E295497
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Borken (Hesse) |
E604598
|
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: Borken (Hesse) | Statement: [Province of Westphalia, containsSettlement, Borken (Hesse)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Borken (Hesse) Context triple: [Province of Westphalia, containsSettlement, Borken (Hesse)]
-
A.
Büttelborn
Büttelborn is a municipality in the Groß-Gerau district of Hesse, Germany, situated in the Rhine-Main region near the city of Darmstadt.
-
B.
Gevelsberg
Gevelsberg is a town in North Rhine-Westphalia, Germany, situated in the Ennepe-Ruhr district within the Ruhr metropolitan region.
-
C.
Niederkassel
Niederkassel is a town in North Rhine-Westphalia, Germany, situated on the right bank of the Rhine between Bonn and Cologne.
-
D.
Gorssel
Gorssel is a village in the Dutch province of Gelderland, known for its scenic rural character and as the location of Museum MORE for modern realism.
-
E.
Borken
chosen
Borken is a town in western Germany that serves as an administrative and commercial center in the state of North Rhine-Westphalia.
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d954a325948190994bcfc9d571a3a8 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65eb71c548190826d243a354bd01c |
completed | May 2, 2026, 8:29 p.m. |
Created at: April 8, 2026, 11:49 p.m.