Triple
T1765997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alb-Donau-Kreis |
E38763
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Nellingen
Nellingen is a small municipality in the Alb-Donau district of the German state of Baden-Württemberg, situated on the Swabian Jura plateau.
|
E205605
|
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: Nellingen | Statement: [Alb-Donau-Kreis, hasTown, Nellingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nellingen Context triple: [Alb-Donau-Kreis, hasTown, Nellingen]
-
A.
Teylingen
Teylingen is a municipality in the Dutch province of South Holland, known for its historic estates and proximity to the bulb-growing region.
-
B.
Etten-Leur
Etten-Leur is a town and municipality in the southern Netherlands known for its historical connection to Vincent van Gogh and its location near the city of Breda.
-
C.
Nieuwendijk
Nieuwendijk is one of Amsterdam’s oldest and busiest shopping streets, running through the historic city center near Dam Square.
-
D.
Nissewaard
Nissewaard is a municipality and town in the western Netherlands, located on the island of Voorne-Putten in the province of South Holland.
-
E.
Beinsdorp
Beinsdorp is a small village in the Dutch province of North Holland, situated within the municipality of Haarlemmermeer.
- 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: Nellingen Triple: [Alb-Donau-Kreis, hasTown, Nellingen]
Generated description
Nellingen is a small municipality in the Alb-Donau district of the German state of Baden-Württemberg, situated on the Swabian Jura plateau.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nellingen Target entity description: Nellingen is a small municipality in the Alb-Donau district of the German state of Baden-Württemberg, situated on the Swabian Jura plateau.
-
A.
Teylingen
Teylingen is a municipality in the Dutch province of South Holland, known for its historic estates and proximity to the bulb-growing region.
-
B.
Etten-Leur
Etten-Leur is a town and municipality in the southern Netherlands known for its historical connection to Vincent van Gogh and its location near the city of Breda.
-
C.
Nieuwendijk
Nieuwendijk is one of Amsterdam’s oldest and busiest shopping streets, running through the historic city center near Dam Square.
-
D.
Nissewaard
Nissewaard is a municipality and town in the western Netherlands, located on the island of Voorne-Putten in the province of South Holland.
-
E.
Beinsdorp
Beinsdorp is a small village in the Dutch province of North Holland, situated within the municipality of Haarlemmermeer.
- 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_69a8862d562481908d7025a1c1f67c0d |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa6467c3f08190abc8a06269ede908 |
completed | March 6, 2026, 5:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adc9a14a18819090b83b3d10304c74 |
completed | March 8, 2026, 7:10 p.m. |
| NEDg | Description generation | batch_69adcaed1f788190b14c3e2d2c3036d9 |
completed | March 8, 2026, 7:15 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adcbee97e88190adc1315c0a5013ab |
completed | March 8, 2026, 7:20 p.m. |
Created at: March 4, 2026, 7:31 p.m.