Triple
T9641638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fürstenfeldbruck district |
E233084
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Hattenhofen
Hattenhofen is a small municipality in the Upper Bavarian region of Germany, situated west of Munich in a predominantly rural area.
|
E836608
|
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: Hattenhofen | Statement: [Fürstenfeldbruck district, contains, Hattenhofen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hattenhofen Context triple: [Fürstenfeldbruck district, contains, Hattenhofen]
-
A.
Schlagenhofen
Schlagenhofen is a small village in Bavaria, Germany, that forms part of the municipality of Inning am Ammersee near Lake Ammersee.
-
B.
Attenhofen
Attenhofen is a small municipality in the Bavarian region of Germany, known for its rural character and local agriculture.
-
C.
Diedenhofen
Diedenhofen is the historical German name for the town of Thionville in northeastern France, near the border with Luxembourg and Germany.
-
D.
Hägendorf
Hägendorf is a municipality in the canton of Solothurn in northwestern Switzerland, known for its residential character and proximity to the Jura mountains.
-
E.
Gerolzhofen
Gerolzhofen is a small historic town in northern Bavaria, Germany, known for its medieval architecture and wine-growing surroundings.
- 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: Hattenhofen Triple: [Fürstenfeldbruck district, contains, Hattenhofen]
Generated description
Hattenhofen is a small municipality in the Upper Bavarian region of Germany, situated west of Munich in a predominantly rural area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hattenhofen Target entity description: Hattenhofen is a small municipality in the Upper Bavarian region of Germany, situated west of Munich in a predominantly rural area.
-
A.
Schlagenhofen
Schlagenhofen is a small village in Bavaria, Germany, that forms part of the municipality of Inning am Ammersee near Lake Ammersee.
-
B.
Attenhofen
Attenhofen is a small municipality in the Bavarian region of Germany, known for its rural character and local agriculture.
-
C.
Diedenhofen
Diedenhofen is the historical German name for the town of Thionville in northeastern France, near the border with Luxembourg and Germany.
-
D.
Hägendorf
Hägendorf is a municipality in the canton of Solothurn in northwestern Switzerland, known for its residential character and proximity to the Jura mountains.
-
E.
Gerolzhofen
Gerolzhofen is a small historic town in northern Bavaria, Germany, known for its medieval architecture and wine-growing surroundings.
- 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_69ca848a5a908190aad251f4137b0c3a |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9b566a2881909ab3f9502b1c3c8d |
completed | April 1, 2026, 10:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d28194f6e88190932efe607088394a |
completed | April 5, 2026, 3:36 p.m. |
| NEDg | Description generation | batch_69d282fd10248190a1a0b4573b2065ae |
completed | April 5, 2026, 3:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d283d0e1748190a0c65bbaa8e8348e |
completed | April 5, 2026, 3:46 p.m. |
Created at: March 30, 2026, 8:12 p.m.