Triple
T18708003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kniphausen |
E457422
|
entity |
| Predicate | hasNameInLanguage |
P15
|
FINISHED |
| Object |
Kniphausen (German)
Kniphausen (German) is the German name for a locality or historical territory in northern Germany, likely associated with the region of East Frisia.
|
E1338476
|
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: Kniphausen (German) | Statement: [Kniphausen, hasNameInLanguage, Kniphausen (German)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kniphausen (German) Context triple: [Kniphausen, hasNameInLanguage, Kniphausen (German)]
-
A.
Krönau (German)
Krönau is the historical German name for the Slovak village of Ivanka pri Dunaji, located near Bratislava.
-
B.
Lippinghausen
Lippinghausen is a locality within the municipality of Hiddenhausen in the German state of North Rhine-Westphalia.
-
C.
Dinkelscherben
Dinkelscherben is a municipality in the Swabian region of Bavaria in southern Germany.
-
D.
Braunlage
Braunlage is a German town and ski resort in the Harz Mountains, known for its winter sports, hiking opportunities, and scenic natural surroundings.
-
E.
Kienbaum
Kienbaum is a small village in the municipality of Grünheide (Mark) in Brandenburg, Germany, known in part for its nearby national Olympic training center.
- 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: Kniphausen (German) Triple: [Kniphausen, hasNameInLanguage, Kniphausen (German)]
Generated description
Kniphausen (German) is the German name for a locality or historical territory in northern Germany, likely associated with the region of East Frisia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kniphausen (German) Target entity description: Kniphausen (German) is the German name for a locality or historical territory in northern Germany, likely associated with the region of East Frisia.
-
A.
Krönau (German)
Krönau is the historical German name for the Slovak village of Ivanka pri Dunaji, located near Bratislava.
-
B.
Lippinghausen
Lippinghausen is a locality within the municipality of Hiddenhausen in the German state of North Rhine-Westphalia.
-
C.
Dinkelscherben
Dinkelscherben is a municipality in the Swabian region of Bavaria in southern Germany.
-
D.
Braunlage
Braunlage is a German town and ski resort in the Harz Mountains, known for its winter sports, hiking opportunities, and scenic natural surroundings.
-
E.
Kienbaum
Kienbaum is a small village in the municipality of Grünheide (Mark) in Brandenburg, Germany, known in part for its nearby national Olympic training center.
- 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_69d8d392aad081909fe31aa03e6e97d1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56719383481909d68c9e873ca0800 |
completed | April 19, 2026, 11:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a052b3c8e5081908735b95498b49547 |
completed | May 14, 2026, 1:54 a.m. |
| NEDg | Description generation | batch_6a052c70dca881908fd4f3a437340bb5 |
completed | May 14, 2026, 1:59 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a052cc1c634819095ebfebf54d784d0 |
completed | May 14, 2026, 2 a.m. |
Created at: April 10, 2026, 11:50 a.m.