Triple
T19846426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Limburg-Weilburg |
E476870
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Hadamar |
—
|
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: Hadamar | Statement: [Limburg-Weilburg, contains, Hadamar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hadamar Context triple: [Limburg-Weilburg, contains, Hadamar]
-
A.
Hadamar
chosen
Hadamar is a small town in the German state of Hesse, historically notable as a former Nassau residence and later as the site of a World War II euthanasia center.
-
B.
Beelitz
Beelitz is a small German town in the state of Brandenburg, best known for its historic asparagus cultivation and the nearby Beelitz-Heilstätten sanatorium complex.
-
C.
Bogheim
Bogheim is a small village in North Rhine-Westphalia, Germany, that forms part of the municipality of Kreuzau in the Düren district.
-
D.
Gehrden
Gehrden is a small town in Lower Saxony, Germany, located near Hanover and known for its surrounding rural villages and scenic landscapes.
-
E.
Blasewitz
Blasewitz is a historic and affluent district of Dresden, Germany, known for its riverside villas and location along the Elbe River.
- 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_69d8e51d39d081909bcfafeaaf3d2fcc |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65809da2c8190bb579ef42513b74d |
completed | April 20, 2026, 4:44 p.m. |
Created at: April 10, 2026, 1:51 p.m.