Triple
T12877826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leipzig metropolitan region |
E308012
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Markwerben
Markwerben is a small locality in the German state of Saxony-Anhalt that lies within the broader Leipzig metropolitan region.
|
E1006470
|
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: Markwerben | Statement: [Leipzig metropolitan region, containsCity, Markwerben]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Markwerben Context triple: [Leipzig metropolitan region, containsCity, Markwerben]
-
A.
Helmbrechts
Helmbrechts is a small town in northern Bavaria, Germany, known for its textile industry and location in the Franconian Forest region.
-
B.
Wassenberg
Wassenberg is a historic town in western Germany near the Dutch border, known for its medieval origins and association with the noble House of Wassenberg.
-
C.
Wiehe
Wiehe is a small town in the German state of Thuringia, historically notable as the birthplace of the influential 19th-century historian Leopold von Ranke.
-
D.
Ziegelwerder
Ziegelwerder is an island located within Lake Schwerin in northern Germany.
-
E.
Baumwerder
Baumwerder is a small island located in Tegeler See, a lake in the Berlin district of Reinickendorf, 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: Markwerben Triple: [Leipzig metropolitan region, containsCity, Markwerben]
Generated description
Markwerben is a small locality in the German state of Saxony-Anhalt that lies within the broader Leipzig metropolitan region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Markwerben Target entity description: Markwerben is a small locality in the German state of Saxony-Anhalt that lies within the broader Leipzig metropolitan region.
-
A.
Helmbrechts
Helmbrechts is a small town in northern Bavaria, Germany, known for its textile industry and location in the Franconian Forest region.
-
B.
Wassenberg
Wassenberg is a historic town in western Germany near the Dutch border, known for its medieval origins and association with the noble House of Wassenberg.
-
C.
Wiehe
Wiehe is a small town in the German state of Thuringia, historically notable as the birthplace of the influential 19th-century historian Leopold von Ranke.
-
D.
Ziegelwerder
Ziegelwerder is an island located within Lake Schwerin in northern Germany.
-
E.
Baumwerder
Baumwerder is a small island located in Tegeler See, a lake in the Berlin district of Reinickendorf, 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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d970fa8474819086a8af3c90f3ca84 |
completed | April 10, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69bb83bac8190838f7537b806317c |
completed | May 3, 2026, 12:50 a.m. |
| NEDg | Description generation | batch_69f69cc6fa84819093a4317ab355f62b |
completed | May 3, 2026, 12:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f69d845a9081909b40562825c1c500 |
completed | May 3, 2026, 12:57 a.m. |
Created at: April 9, 2026, 5:38 p.m.