Triple
T19484191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heidenheim district |
E487465
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object | Dischingen |
—
|
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: Dischingen | Statement: [Heidenheim district, containsMunicipality, Dischingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dischingen Context triple: [Heidenheim district, containsMunicipality, Dischingen]
-
A.
Dischingen
chosen
Dischingen is a small municipality in the state of Baden-Württemberg in southern Germany, known for its rural character and location within the Swabian Jura region.
-
B.
Taufkirchen
Taufkirchen is a municipality in Bavaria, Germany, known for its strong aerospace and defense industry presence.
-
C.
Ötlingen
Ötlingen is a village-like district of the town of Weil am Rhein in the southwestern German state of Baden-Württemberg, near the borders with France and Switzerland.
-
D.
Kirchlindach
Kirchlindach is a Swiss municipality in the canton of Bern, known for its rural character and proximity to the city of Bern.
-
E.
Schneizlreuth
Schneizlreuth is a small Bavarian municipality in southeastern Germany, known for its alpine landscapes and location near the Austrian border.
- 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_69d8e8d924388190b847cb15bb3d0aff |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6343dcc748190b0df816e6ab4cafb |
completed | April 20, 2026, 2:12 p.m. |
Created at: April 10, 2026, 1:39 p.m.