Triple
T12566982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Westphalia |
E295497
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Dautphetal |
E877110
|
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: Dautphetal | Statement: [Province of Westphalia, containsSettlement, Dautphetal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dautphetal Context triple: [Province of Westphalia, containsSettlement, Dautphetal]
-
A.
Dautphetal
chosen
Dautphetal is a municipality in the Marburg-Biedenkopf district of Hesse, Germany, known for its rural character and location in the Lahn River valley.
-
B.
Wuhletal
Wuhletal is a valley landscape in Berlin shaped by the course of the Wuhle river, featuring green spaces, walking paths, and recreational areas.
-
C.
Petershausen
Petershausen is a Bavarian municipality in southern Germany, located north of Munich and known for its rural character and good rail connections to the city.
-
D.
Pfeffenhausen
Pfeffenhausen is a market town in Lower Bavaria, Germany, known for its rural character and location within the Landshut district.
-
E.
Wallenfels
Wallenfels is a small town in northern Bavaria, Germany, known for its scenic location in the Franconian Forest region.
- 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_69f7b05474bc8190a42e2a9540055c47 |
completed | May 3, 2026, 8:30 p.m. |
Created at: April 8, 2026, 11:49 p.m.