Triple
T12877887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leipzig metropolitan region |
E308012
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Thallwitz
Thallwitz is a small municipality in the German state of Saxony, situated within the broader Leipzig metropolitan area.
|
E1006487
|
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: Thallwitz | Statement: [Leipzig metropolitan region, containsCity, Thallwitz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thallwitz Context triple: [Leipzig metropolitan region, containsCity, Thallwitz]
-
A.
Blasewitz
Blasewitz is a historic and affluent district of Dresden, Germany, known for its riverside villas and location along the Elbe River.
-
B.
Seelitz
Seelitz is a municipality in the Free State of Saxony in eastern Germany, known for its rural character and location within the Mittelsachsen region.
-
C.
Kasendorf
Kasendorf is a small municipality in the Upper Franconia region of Bavaria, Germany, known for its rural character and scenic surroundings.
-
D.
Tattendorf
Tattendorf is a small wine-growing village and municipality in Lower Austria, known for its vineyards and rural character.
-
E.
Ohlendorf
Ohlendorf is a German surname most notably associated with Otto Ohlendorf, a high-ranking Nazi SS officer and war criminal.
- 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: Thallwitz Triple: [Leipzig metropolitan region, containsCity, Thallwitz]
Generated description
Thallwitz is a small municipality in the German state of Saxony, situated within the broader Leipzig metropolitan area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Thallwitz Target entity description: Thallwitz is a small municipality in the German state of Saxony, situated within the broader Leipzig metropolitan area.
-
A.
Blasewitz
Blasewitz is a historic and affluent district of Dresden, Germany, known for its riverside villas and location along the Elbe River.
-
B.
Seelitz
Seelitz is a municipality in the Free State of Saxony in eastern Germany, known for its rural character and location within the Mittelsachsen region.
-
C.
Kasendorf
Kasendorf is a small municipality in the Upper Franconia region of Bavaria, Germany, known for its rural character and scenic surroundings.
-
D.
Tattendorf
Tattendorf is a small wine-growing village and municipality in Lower Austria, known for its vineyards and rural character.
-
E.
Ohlendorf
Ohlendorf is a German surname most notably associated with Otto Ohlendorf, a high-ranking Nazi SS officer and war criminal.
- 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.