Triple
T14378971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philipp Marheineke |
E356550
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Marheineke
Marheineke is a German surname most notably associated with the 19th-century Protestant theologian Philipp Marheineke.
|
E1096030
|
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: Marheineke | Statement: [Philipp Marheineke, familyName, Marheineke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marheineke Context triple: [Philipp Marheineke, familyName, Marheineke]
-
A.
Bramsche
Bramsche is a town in Lower Saxony, Germany, known for its location near Osnabrück and its historical textile industry.
-
B.
Wiedensahl
Wiedensahl is a small village in Lower Saxony, Germany, best known as the birthplace of the humorist and illustrator Wilhelm Busch.
-
C.
Reichardtswerben
Reichardtswerben is a small municipality in the Weißenfels area of Saxony-Anhalt in eastern Germany.
-
D.
Bischoffen
Bischoffen is a small municipality in the central German state of Hesse, situated in a rural area characterized by forests, hills, and nearby reservoirs.
-
E.
Schwanebeck
Schwanebeck is a former municipality in Brandenburg, Germany, that now forms part of the town of Panketal.
- 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: Marheineke Triple: [Philipp Marheineke, familyName, Marheineke]
Generated description
Marheineke is a German surname most notably associated with the 19th-century Protestant theologian Philipp Marheineke.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Marheineke Target entity description: Marheineke is a German surname most notably associated with the 19th-century Protestant theologian Philipp Marheineke.
-
A.
Bramsche
Bramsche is a town in Lower Saxony, Germany, known for its location near Osnabrück and its historical textile industry.
-
B.
Wiedensahl
Wiedensahl is a small village in Lower Saxony, Germany, best known as the birthplace of the humorist and illustrator Wilhelm Busch.
-
C.
Reichardtswerben
Reichardtswerben is a small municipality in the Weißenfels area of Saxony-Anhalt in eastern Germany.
-
D.
Bischoffen
Bischoffen is a small municipality in the central German state of Hesse, situated in a rural area characterized by forests, hills, and nearby reservoirs.
-
E.
Schwanebeck
Schwanebeck is a former municipality in Brandenburg, Germany, that now forms part of the town of Panketal.
- 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de900a67e08190ab1dcf36e6bb3405 |
completed | April 14, 2026, 7:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4c5728fc819089ef3c7c34b10101 |
completed | May 8, 2026, 2:37 a.m. |
| NEDg | Description generation | batch_69fd4e4bae188190a8d1c5b833d58cd8 |
completed | May 8, 2026, 2:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd4f5782b4819081d32dbef032ac61 |
completed | May 8, 2026, 2:49 a.m. |
Created at: April 10, 2026, 1:16 a.m.