Triple
T16124965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aichach-Friedberg |
E391244
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Inchenhofen
Inchenhofen is a small municipality in the Aichach-Friedberg district of Bavaria in southern Germany.
|
E1196029
|
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: Inchenhofen | Statement: [Aichach-Friedberg, hasMunicipality, Inchenhofen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Inchenhofen Context triple: [Aichach-Friedberg, hasMunicipality, Inchenhofen]
-
A.
Wehofen
Wehofen is a district of the Walsum area in the city of Duisburg in North Rhine-Westphalia, Germany.
-
B.
Hemhofen
Hemhofen is a small municipality in the Erlangen-Höchstadt district of Bavaria, Germany.
-
C.
Schwabniederhofen
Schwabniederhofen is a small municipality located in the Weilheim-Schongau district of Bavaria in southern Germany.
-
D.
Diedenhofen
Diedenhofen is the historical German name for the town of Thionville in northeastern France, near the border with Luxembourg and Germany.
-
E.
Reichertshofen
Reichertshofen is a market town and municipality in Upper Bavaria, Germany, known for its location near the confluence of the Paar and Ilm rivers and its proximity to the city of Ingolstadt.
- 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: Inchenhofen Triple: [Aichach-Friedberg, hasMunicipality, Inchenhofen]
Generated description
Inchenhofen is a small municipality in the Aichach-Friedberg district of Bavaria in southern Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Inchenhofen Target entity description: Inchenhofen is a small municipality in the Aichach-Friedberg district of Bavaria in southern Germany.
-
A.
Wehofen
Wehofen is a district of the Walsum area in the city of Duisburg in North Rhine-Westphalia, Germany.
-
B.
Hemhofen
Hemhofen is a small municipality in the Erlangen-Höchstadt district of Bavaria, Germany.
-
C.
Schwabniederhofen
Schwabniederhofen is a small municipality located in the Weilheim-Schongau district of Bavaria in southern Germany.
-
D.
Diedenhofen
Diedenhofen is the historical German name for the town of Thionville in northeastern France, near the border with Luxembourg and Germany.
-
E.
Reichertshofen
Reichertshofen is a market town and municipality in Upper Bavaria, Germany, known for its location near the confluence of the Paar and Ilm rivers and its proximity to the city of Ingolstadt.
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2020408a88190bf3dfc893d577c55 |
completed | April 17, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff2a9db848190bafb959bd7511246 |
completed | May 10, 2026, 2:51 a.m. |
| NEDg | Description generation | batch_69fff3b375d48190a958b34c5df5c5f1 |
completed | May 10, 2026, 2:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fff447e1248190a3a1386946172429 |
completed | May 10, 2026, 2:58 a.m. |
Created at: April 10, 2026, 5 a.m.