Triple
T635077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eberhard Schöngarth |
E16605
|
entity |
| Predicate | placeOfDeath |
P21
|
FINISHED |
| Object |
Hameln
Hameln is a historic town in Lower Saxony, Germany, best known as the setting of the Pied Piper of Hamelin legend.
|
E178114
|
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: Hameln | Statement: [Eberhard Schöngarth, placeOfDeath, Hameln]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hameln Context triple: [Eberhard Schöngarth, placeOfDeath, Hameln]
-
A.
Hildesheim
Hildesheim is a historic city in northern Germany renowned for its medieval architecture and UNESCO-listed Romanesque churches.
-
B.
Wolfenbüttel
Wolfenbüttel is a historic town in Lower Saxony, Germany, known for its Renaissance castle and rich cultural heritage.
-
C.
Lüneburg
Lüneburg is a historic Hanseatic town in northern Germany renowned for its medieval architecture and former wealth from salt mining.
-
D.
Delmenhorst
Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
-
E.
Wernigerode
Wernigerode is a picturesque German town in Saxony-Anhalt known for its colorful half-timbered houses, medieval castle, and location on the northern slopes of the Harz Mountains.
- 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: Hameln Triple: [Eberhard Schöngarth, placeOfDeath, Hameln]
Generated description
Hameln is a historic town in Lower Saxony, Germany, best known as the setting of the Pied Piper of Hamelin legend.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hameln Target entity description: Hameln is a historic town in Lower Saxony, Germany, best known as the setting of the Pied Piper of Hamelin legend.
-
A.
Hildesheim
Hildesheim is a historic city in northern Germany renowned for its medieval architecture and UNESCO-listed Romanesque churches.
-
B.
Wolfenbüttel
Wolfenbüttel is a historic town in Lower Saxony, Germany, known for its Renaissance castle and rich cultural heritage.
-
C.
Lüneburg
Lüneburg is a historic Hanseatic town in northern Germany renowned for its medieval architecture and former wealth from salt mining.
-
D.
Delmenhorst
Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
-
E.
Wernigerode
Wernigerode is a picturesque German town in Saxony-Anhalt known for its colorful half-timbered houses, medieval castle, and location on the northern slopes of the Harz Mountains.
- 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_69a4936be1c88190af56540324b57da7 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49ee4ee8481908ad45405e3f3835c |
completed | March 1, 2026, 8:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad36eddeb881908e3ba76969c1b24c |
completed | March 8, 2026, 8:44 a.m. |
| NEDg | Description generation | batch_69ad38dd6e98819082ceba12e9280963 |
completed | March 8, 2026, 8:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad3a71919c8190822efc93501f15ef |
completed | March 8, 2026, 8:59 a.m. |
Created at: March 1, 2026, 7:35 p.m.