Triple
T20667830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freising district |
E507938
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Nandlstadt
Nandlstadt is a market town in Bavaria, Germany, known as one of the oldest hop-growing areas in the world.
|
E1456148
|
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: Nandlstadt | Statement: [Freising district, contains, Nandlstadt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nandlstadt Context triple: [Freising district, contains, Nandlstadt]
-
A.
Weiterstadt
Weiterstadt is a town in the German state of Hesse, located near Darmstadt and known for its residential areas and commercial centers.
-
B.
Weinstadt
Weinstadt is a town in the German state of Baden-Württemberg, known for its winegrowing tradition in the Rems Valley near Stuttgart.
-
C.
Nettelstädt
Nettelstädt is a locality within the town of Rüthen in the district of Soest, North Rhine-Westphalia, Germany.
-
D.
Schwalmstadt
Schwalmstadt is a small town in the Schwalm-Eder district of northern Hesse, Germany, known for its historic half-timbered architecture and picturesque setting in the Schwalm River valley.
-
E.
Greifenburg
Greifenburg is a small market town in the Austrian state of Carinthia, known for its alpine setting and popularity as a paragliding and outdoor recreation destination.
- 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: Nandlstadt Triple: [Freising district, contains, Nandlstadt]
Generated description
Nandlstadt is a market town in Bavaria, Germany, known as one of the oldest hop-growing areas in the world.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nandlstadt Target entity description: Nandlstadt is a market town in Bavaria, Germany, known as one of the oldest hop-growing areas in the world.
-
A.
Weiterstadt
Weiterstadt is a town in the German state of Hesse, located near Darmstadt and known for its residential areas and commercial centers.
-
B.
Weinstadt
Weinstadt is a town in the German state of Baden-Württemberg, known for its winegrowing tradition in the Rems Valley near Stuttgart.
-
C.
Nettelstädt
Nettelstädt is a locality within the town of Rüthen in the district of Soest, North Rhine-Westphalia, Germany.
-
D.
Schwalmstadt
Schwalmstadt is a small town in the Schwalm-Eder district of northern Hesse, Germany, known for its historic half-timbered architecture and picturesque setting in the Schwalm River valley.
-
E.
Greifenburg
Greifenburg is a small market town in the Austrian state of Carinthia, known for its alpine setting and popularity as a paragliding and outdoor recreation destination.
- 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_69e0b4c059bc81908ea762cd73ea4424 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b5c4c4608190ae17da4a59e5ae80 |
completed | April 20, 2026, 11:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0918b6f4788190838893fac16ab4cf |
completed | May 17, 2026, 1:24 a.m. |
| NEDg | Description generation | batch_6a0919608d148190aaf1abee12fe8935 |
completed | May 17, 2026, 1:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0919f58008819097e05a187ed4b3de |
completed | May 17, 2026, 1:29 a.m. |
Created at: April 16, 2026, 11:44 a.m.