Triple
T12887129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darmstadt-Dieburg |
E308256
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Eppertshausen
Eppertshausen is a small municipality in the German state of Hesse, located southeast of Frankfurt am Main.
|
E1100793
|
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: Eppertshausen | Statement: [Darmstadt-Dieburg, contains, Eppertshausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eppertshausen Context triple: [Darmstadt-Dieburg, contains, Eppertshausen]
-
A.
Pfeffenhausen
Pfeffenhausen is a market town in Lower Bavaria, Germany, known for its rural character and location within the Landshut district.
-
B.
Fürstenzell
Fürstenzell is a market town and municipality in Lower Bavaria, Germany, known for its historic monastery and rural setting near the city of Passau.
-
C.
Odelzhausen
Odelzhausen is a municipality in Bavaria, Germany, known for its historic castle and location along the Autobahn between Munich and Augsburg.
-
D.
Herzogenaurach
Herzogenaurach is a Bavarian town in Germany best known as the birthplace and headquarters of the global sportswear brands Adidas and Puma.
-
E.
Grafenrheinfeld
Grafenrheinfeld is a small Bavarian town best known for hosting the former Grafenrheinfeld nuclear power plant on the Main River in northern Germany.
- 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: Eppertshausen Triple: [Darmstadt-Dieburg, contains, Eppertshausen]
Generated description
Eppertshausen is a small municipality in the German state of Hesse, located southeast of Frankfurt am Main.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Eppertshausen Target entity description: Eppertshausen is a small municipality in the German state of Hesse, located southeast of Frankfurt am Main.
-
A.
Pfeffenhausen
Pfeffenhausen is a market town in Lower Bavaria, Germany, known for its rural character and location within the Landshut district.
-
B.
Fürstenzell
Fürstenzell is a market town and municipality in Lower Bavaria, Germany, known for its historic monastery and rural setting near the city of Passau.
-
C.
Odelzhausen
Odelzhausen is a municipality in Bavaria, Germany, known for its historic castle and location along the Autobahn between Munich and Augsburg.
-
D.
Herzogenaurach
Herzogenaurach is a Bavarian town in Germany best known as the birthplace and headquarters of the global sportswear brands Adidas and Puma.
-
E.
Grafenrheinfeld
Grafenrheinfeld is a small Bavarian town best known for hosting the former Grafenrheinfeld nuclear power plant on the Main River in northern Germany.
- 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_69fd646ee860819083277b15aaf510fd |
completed | May 8, 2026, 4:19 a.m. |
| NEDg | Description generation | batch_69fd666a21d48190932a0a91f81490b4 |
completed | May 8, 2026, 4:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd66d75974819084aa4eb48f7079a3 |
completed | May 8, 2026, 4:30 a.m. |
Created at: April 9, 2026, 5:39 p.m.