Triple
T8680972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beilstein |
E206035
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Lahn-Dill-Kreis |
E227605
|
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: Lahn-Dill-Kreis | Statement: [Beilstein, partOf, Lahn-Dill-Kreis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lahn-Dill-Kreis Context triple: [Beilstein, partOf, Lahn-Dill-Kreis]
-
A.
Lahn-Dill-Kreis
chosen
Lahn-Dill-Kreis is a rural district in the state of Hesse, Germany, known for its mix of industrial towns and scenic landscapes along the Lahn and Dill rivers.
-
B.
Saalekreis
Saalekreis is a rural district in the German state of Saxony-Anhalt, located around the city of Halle (Saale).
-
C.
Saale-Holzland-Kreis
Saale-Holzland-Kreis is a rural district in the eastern German state of Thuringia, known for its scenic Saale River valley, historic towns, and mixed agricultural and forested landscapes.
-
D.
Saale-Orla-Kreis
Saale-Orla-Kreis is a rural district in the state of Thuringia in eastern Germany, known for its river valleys, rolling hills, and small historic towns.
-
E.
Hochtaunuskreis
Hochtaunuskreis is a rural district in the German state of Hesse, known for its affluent communities, scenic landscapes, and location in the Taunus mountain region north of Frankfurt.
- 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_69ca835379688190aa06b9d98e684d58 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc4ae6d19c8190be003f7901c0468d |
completed | March 31, 2026, 10:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d100a931988190aaff56f16057ea90 |
completed | April 4, 2026, 12:14 p.m. |
Created at: March 30, 2026, 6:32 p.m.