Triple
T2620107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David E. Lilienthal |
E58986
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Lilienthal
Lilienthal is a German-origin surname borne by various notable individuals, including figures in aviation, science, and public service.
|
E303044
|
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: Lilienthal | Statement: [David E. Lilienthal, familyName, Lilienthal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lilienthal Context triple: [David E. Lilienthal, familyName, Lilienthal]
-
A.
Lippendorf
Lippendorf is a village in Saxony, Germany, historically notable as the birthplace of Katharina von Bora, the wife of Martin Luther.
-
B.
Idstein
Idstein is a historic town in the German state of Hesse, known for its well-preserved medieval old town and timber-framed architecture.
-
C.
Lankwitz
Lankwitz is a residential locality in the southwestern part of Berlin, known for its quiet neighborhoods, green spaces, and mix of historic and modern architecture.
-
D.
Neustadt
Neustadt is a district of the Austrian city of Salzburg, known for its central urban character within the historic and cultural landscape of the city.
-
E.
Neustadt
Neustadt is a vibrant district of Dresden, Germany, known for its historic architecture, lively arts scene, and numerous bars, cafes, and cultural venues.
- 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: Lilienthal Triple: [David E. Lilienthal, familyName, Lilienthal]
Generated description
Lilienthal is a German-origin surname borne by various notable individuals, including figures in aviation, science, and public service.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lilienthal Target entity description: Lilienthal is a German-origin surname borne by various notable individuals, including figures in aviation, science, and public service.
-
A.
Lippendorf
Lippendorf is a village in Saxony, Germany, historically notable as the birthplace of Katharina von Bora, the wife of Martin Luther.
-
B.
Idstein
Idstein is a historic town in the German state of Hesse, known for its well-preserved medieval old town and timber-framed architecture.
-
C.
Lankwitz
Lankwitz is a residential locality in the southwestern part of Berlin, known for its quiet neighborhoods, green spaces, and mix of historic and modern architecture.
-
D.
Neustadt
Neustadt is a district of the Austrian city of Salzburg, known for its central urban character within the historic and cultural landscape of the city.
-
E.
Neustadt
Neustadt is a vibrant district of Dresden, Germany, known for its historic architecture, lively arts scene, and numerous bars, cafes, and cultural venues.
- 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_69ab4ac444dc819099614e534dd6021f |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd897acb481909a976b70304cc30e |
completed | March 7, 2026, 7:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afe88781ec8190a13784501208c5a5 |
completed | March 10, 2026, 9:46 a.m. |
| NEDg | Description generation | batch_69afebdb8ec8819099878d0a61857efb |
completed | March 10, 2026, 10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b0039dd22881909a90070a3d490df1 |
completed | March 10, 2026, 11:42 a.m. |
Created at: March 6, 2026, 9:50 p.m.