Triple
T633340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German Aerospace Center |
E15966
|
entity |
| Predicate | hasResearchCenterIn |
P11730
|
FINISHED |
| Object |
Trauen
Trauen is a village in Lower Saxony, Germany, known for hosting a research facility of the German Aerospace Center (DLR).
|
E79621
|
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: Trauen | Statement: [German Aerospace Center, hasResearchCenterIn, Trauen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trauen Context triple: [German Aerospace Center, hasResearchCenterIn, Trauen]
-
A.
Mohrungen
Mohrungen is a historic town in former East Prussia (now Morąg in northern Poland), known as the birthplace of philosopher and theologian Johann Gottfried Herder.
-
B.
Bad Tölz
Bad Tölz is a Bavarian spa town in southern Germany known for its historic old town, alpine scenery, and traditional German architecture.
-
C.
Fürth
Fürth is a historic city in northern Bavaria, Germany, known for its well-preserved old town and proximity to Nuremberg within the Franconian metropolitan region.
-
D.
Sieber
Sieber is a small river in the German state of Lower Saxony that flows through the Harz Mountains and into the Oder.
-
E.
Escharen
Escharen is a village in the Dutch province of North Brabant that was formerly an independent municipality before being incorporated into a larger administrative unit.
- 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: Trauen Triple: [German Aerospace Center, hasResearchCenterIn, Trauen]
Generated description
Trauen is a village in Lower Saxony, Germany, known for hosting a research facility of the German Aerospace Center (DLR).
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Trauen Target entity description: Trauen is a village in Lower Saxony, Germany, known for hosting a research facility of the German Aerospace Center (DLR).
-
A.
Mohrungen
Mohrungen is a historic town in former East Prussia (now Morąg in northern Poland), known as the birthplace of philosopher and theologian Johann Gottfried Herder.
-
B.
Bad Tölz
Bad Tölz is a Bavarian spa town in southern Germany known for its historic old town, alpine scenery, and traditional German architecture.
-
C.
Fürth
Fürth is a historic city in northern Bavaria, Germany, known for its well-preserved old town and proximity to Nuremberg within the Franconian metropolitan region.
-
D.
Sieber
Sieber is a small river in the German state of Lower Saxony that flows through the Harz Mountains and into the Oder.
-
E.
Escharen
Escharen is a village in the Dutch province of North Brabant that was formerly an independent municipality before being incorporated into a larger administrative unit.
- 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_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a515ceb081908c064b2082047c0f |
completed | March 1, 2026, 8:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a56ef052308190bfaed448c3737ef6 |
completed | March 2, 2026, 11:05 a.m. |
| NEDg | Description generation | batch_69a56f5668108190910db85f3beb5eed |
completed | March 2, 2026, 11:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a5733acb188190b4cdd12ed3a96860 |
completed | March 2, 2026, 11:23 a.m. |
Created at: March 1, 2026, 7:35 p.m.