Triple
T12566890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Westphalia |
E295497
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Holzwickede |
E456761
|
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: Holzwickede | Statement: [Province of Westphalia, containsSettlement, Holzwickede]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Holzwickede Context triple: [Province of Westphalia, containsSettlement, Holzwickede]
-
A.
Holzwickede
chosen
Holzwickede is a small municipality in North Rhine-Westphalia, Germany, situated near the city of Dortmund and known for its residential character and proximity to major transport links.
-
B.
Osterwieck
Osterwieck is a historic town in the German state of Saxony-Anhalt, known for its well-preserved medieval architecture and location on the northern edge of the Harz Mountains.
-
C.
Nordwalde
Nordwalde is a small municipality in North Rhine-Westphalia, Germany, known for its rural character and proximity to the city of Münster.
-
D.
Hasselwerder
Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
-
E.
Niederschöneweide
Niederschöneweide is a locality in the Berlin borough of Treptow-Köpenick, known for its riverside setting along the Spree and its mix of residential areas and former industrial sites.
- 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_69f655914f908190afbebbec3cb57e73 |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 8, 2026, 11:49 p.m.