Triple
T6046384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giengen an der Brenz |
E134675
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Hürben
Hürben is a district of the town Giengen an der Brenz in the state of Baden-Württemberg, Germany.
|
E595077
|
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: Hürben | Statement: [Giengen an der Brenz, hasSubdivision, Hürben]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hürben Context triple: [Giengen an der Brenz, hasSubdivision, Hürben]
-
A.
Hubersdorf
Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
-
B.
Tussenhausen
Tussenhausen is a municipality in the district of Unterallgäu in Bavaria, Germany, known for its rural character and small villages such as Mattsies.
-
C.
Günsberg
Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
-
D.
Ziegenhain
Ziegenhain is a historic town in the German state of Hesse, known for its medieval fortifications and role in regional conflicts.
-
E.
Tureberg
Tureberg is a central district in Sollentuna Municipality, Sweden, known for housing the municipal center and key public services.
- 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: Hürben Triple: [Giengen an der Brenz, hasSubdivision, Hürben]
Generated description
Hürben is a district of the town Giengen an der Brenz in the state of Baden-Württemberg, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hürben Target entity description: Hürben is a district of the town Giengen an der Brenz in the state of Baden-Württemberg, Germany.
-
A.
Hubersdorf
Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
-
B.
Tussenhausen
Tussenhausen is a municipality in the district of Unterallgäu in Bavaria, Germany, known for its rural character and small villages such as Mattsies.
-
C.
Günsberg
Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
-
D.
Ziegenhain
Ziegenhain is a historic town in the German state of Hesse, known for its medieval fortifications and role in regional conflicts.
-
E.
Tureberg
Tureberg is a central district in Sollentuna Municipality, Sweden, known for housing the municipal center and key public services.
- 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_69c00876a69881908088a2626d3b2666 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056e53f508190864be04bc016c525 |
completed | March 22, 2026, 8:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c64b9acb1c8190a51e540371e20bde |
completed | March 27, 2026, 9:19 a.m. |
| NEDg | Description generation | batch_69c64d52cf8081908b797a68217a4341 |
completed | March 27, 2026, 9:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c64e2adf448190829c2a86c4e483eb |
completed | March 27, 2026, 9:30 a.m. |
Created at: March 22, 2026, 4:09 p.m.