Triple
T5027009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Konstanz (district) |
E113199
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Hilzingen
Hilzingen is a municipality in the state of Baden-Württemberg in southwestern Germany, near the Swiss border.
|
E492513
|
NE FINISHED |
How this triple was built (4 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: Hilzingen | Statement: [Konstanz (district), hasMunicipality, Hilzingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hilzingen Context triple: [Konstanz (district), hasMunicipality, Hilzingen]
-
A.
Bissingen
Bissingen is a suburb of the town of Herbrechtingen in the state of Baden-Württemberg, Germany.
-
B.
Gernsbach
Gernsbach is a historic town in southwestern Germany’s Black Forest region, known for its medieval old town and picturesque setting along the Murg River.
-
C.
Büllingen
Büllingen is a municipality in eastern Belgium’s German-speaking Community, known for its rural landscape and proximity to the historically significant Elsenborn Ridge.
-
D.
Marlenheim
Marlenheim is a commune in northeastern France’s Alsace region, known as a historic wine-producing village and gateway to the area’s renowned vineyards and scenic countryside.
-
E.
Hettstadt
Hettstadt is a small municipality in the Würzburg district of Bavaria, Germany, known for its rural character and proximity to the city of Würzburg.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Hilzingen Triple: [Konstanz (district), hasMunicipality, Hilzingen]
Generated description
Hilzingen is a municipality in the state of Baden-Württemberg in southwestern Germany, near the Swiss border.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hilzingen Target entity description: Hilzingen is a municipality in the state of Baden-Württemberg in southwestern Germany, near the Swiss border.
-
A.
Bissingen
Bissingen is a suburb of the town of Herbrechtingen in the state of Baden-Württemberg, Germany.
-
B.
Gernsbach
Gernsbach is a historic town in southwestern Germany’s Black Forest region, known for its medieval old town and picturesque setting along the Murg River.
-
C.
Büllingen
Büllingen is a municipality in eastern Belgium’s German-speaking Community, known for its rural landscape and proximity to the historically significant Elsenborn Ridge.
-
D.
Marlenheim
Marlenheim is a commune in northeastern France’s Alsace region, known as a historic wine-producing village and gateway to the area’s renowned vineyards and scenic countryside.
-
E.
Hettstadt
Hettstadt is a small municipality in the Würzburg district of Bavaria, Germany, known for its rural character and proximity to the city of Würzburg.
- F. None of above. chosen
Provenance (5 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_69bd443775e48190a646ffbfc4334723 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd738c3aac81908fb6a5c70c97a394 |
completed | March 20, 2026, 4:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beb0ecf0d88190b459d9c29bfc005d |
completed | March 21, 2026, 2:53 p.m. |
| NEDg | Description generation | batch_69beb252ca2c8190b1bf7978b50c7ef6 |
completed | March 21, 2026, 2:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69beb2b989788190b81e6f60398bd49d |
completed | March 21, 2026, 3:01 p.m. |
Created at: March 20, 2026, 1:36 p.m.