Triple
T12887124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darmstadt-Dieburg |
E308256
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Mühltal
Mühltal is a municipality in the Darmstadt-Dieburg district of the German state of Hesse, located near the city of Darmstadt.
|
E1015214
|
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: Mühltal | Statement: [Darmstadt-Dieburg, contains, Mühltal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mühltal Context triple: [Darmstadt-Dieburg, contains, Mühltal]
-
A.
Siegtal
Siegtal is the valley region through which the river Sieg flows in western Germany, known for its scenic landscapes and small towns.
-
B.
Mühlbach
Mühlbach is the former German name of the Romanian city of Sebeș in Transylvania, historically associated with the Transylvanian Saxon community.
-
C.
Eckersbach
Eckersbach is a district of the city of Zwickau in the German state of Saxony, known primarily as a residential area.
-
D.
Mühlengraben
Mühlengraben is a small watercourse in the town of Gifhorn in Lower Saxony, Germany, likely serving as a mill stream or side channel of a larger river.
-
E.
Münstertal
Münstertal is a picturesque municipality in Germany’s Black Forest region, known for its scenic valley landscapes and traditional rural character.
- 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: Mühltal Triple: [Darmstadt-Dieburg, contains, Mühltal]
Generated description
Mühltal is a municipality in the Darmstadt-Dieburg district of the German state of Hesse, located near the city of Darmstadt.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mühltal Target entity description: Mühltal is a municipality in the Darmstadt-Dieburg district of the German state of Hesse, located near the city of Darmstadt.
-
A.
Siegtal
Siegtal is the valley region through which the river Sieg flows in western Germany, known for its scenic landscapes and small towns.
-
B.
Mühlbach
Mühlbach is the former German name of the Romanian city of Sebeș in Transylvania, historically associated with the Transylvanian Saxon community.
-
C.
Eckersbach
Eckersbach is a district of the city of Zwickau in the German state of Saxony, known primarily as a residential area.
-
D.
Mühlengraben
Mühlengraben is a small watercourse in the town of Gifhorn in Lower Saxony, Germany, likely serving as a mill stream or side channel of a larger river.
-
E.
Münstertal
Münstertal is a picturesque municipality in Germany’s Black Forest region, known for its scenic valley landscapes and traditional rural character.
- 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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9714415c08190aa9944b494a3ddad |
completed | April 10, 2026, 9:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c0e54dc48190acf120ca5fe516ab |
completed | May 3, 2026, 3:28 a.m. |
| NEDg | Description generation | batch_69f6c30cf4f88190b0f2cf958df043c0 |
completed | May 3, 2026, 3:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6c38bc0b08190b76cb0853d99ad82 |
completed | May 3, 2026, 3:39 a.m. |
Created at: April 9, 2026, 5:39 p.m.