Triple
T5439123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Konrad Lorenz |
E122086
|
entity |
| Predicate | deathPlace |
P21
|
FINISHED |
| Object |
Altenberg
Altenberg is an Austrian town best known as the longtime home and place of death of Nobel Prize–winning ethologist Konrad Lorenz.
|
E520503
|
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: Altenberg | Statement: [Konrad Lorenz, deathPlace, Altenberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Altenberg Context triple: [Konrad Lorenz, deathPlace, Altenberg]
-
A.
Neuötting
Neuötting is a small Bavarian town in southeastern Germany known for its historic town center and location near the Austrian border.
-
B.
Vöcklabruck
Vöcklabruck is a small historic town in Upper Austria known as a regional center near the Attersee lake and the foothills of the Alps.
-
C.
Olbernhau
Olbernhau is a town in Germany’s Ore Mountains renowned for its traditional woodcraft industry, especially the production of Schwibbogen candle arches and other Christmas decorations.
-
D.
Marchfeld
Marchfeld is a fertile lowland region in eastern Austria known for its intensive agriculture and vegetable production.
-
E.
Kreuth
Kreuth is a Bavarian municipality in southern Germany, known for its alpine landscape and location near Lake Tegernsee in the Bavarian Alps.
- 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: Altenberg Triple: [Konrad Lorenz, deathPlace, Altenberg]
Generated description
Altenberg is an Austrian town best known as the longtime home and place of death of Nobel Prize–winning ethologist Konrad Lorenz.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Altenberg Target entity description: Altenberg is an Austrian town best known as the longtime home and place of death of Nobel Prize–winning ethologist Konrad Lorenz.
-
A.
Neuötting
Neuötting is a small Bavarian town in southeastern Germany known for its historic town center and location near the Austrian border.
-
B.
Vöcklabruck
Vöcklabruck is a small historic town in Upper Austria known as a regional center near the Attersee lake and the foothills of the Alps.
-
C.
Olbernhau
Olbernhau is a town in Germany’s Ore Mountains renowned for its traditional woodcraft industry, especially the production of Schwibbogen candle arches and other Christmas decorations.
-
D.
Marchfeld
Marchfeld is a fertile lowland region in eastern Austria known for its intensive agriculture and vegetable production.
-
E.
Kreuth
Kreuth is a Bavarian municipality in southern Germany, known for its alpine landscape and location near Lake Tegernsee in the Bavarian Alps.
- 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_69bd46400768819092925d461c0b8432 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd91be61dc819087f4a77bdc5ff382 |
completed | March 20, 2026, 6:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf412aa8bc81908d74589b2a38e5eb |
completed | March 22, 2026, 1:08 a.m. |
| NEDg | Description generation | batch_69bf41dd96448190973b7241df5dbb24 |
completed | March 22, 2026, 1:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf42b97d40819087a98c1cc58bb964 |
completed | March 22, 2026, 1:15 a.m. |
Created at: March 20, 2026, 2:07 p.m.