Triple
T10988067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Kissingen (district) |
E259682
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Ramsthal
Ramsthal is a small municipality in the Lower Franconia region of Bavaria, Germany, known for its rural character and winegrowing tradition.
|
E898313
|
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: Ramsthal | Statement: [Bad Kissingen (district), contains, Ramsthal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ramsthal Context triple: [Bad Kissingen (district), contains, Ramsthal]
-
A.
Lothagam
Lothagam is an archaeological and geological site in northern Kenya known for its ancient human burials and prominent rock formations along the western shore of Lake Turkana.
-
B.
Gannat
Gannat is a small town in central France known for its rich paleontological heritage and traditional cultural festivals.
-
C.
Shedgum
Shedgum is a major production area within Saudi Arabia’s vast Ghawar oil field, known for its significant contribution to the country’s crude oil output.
-
D.
Gharaunda
Gharaunda is a town in the Indian state of Haryana known for its agricultural market and proximity to the historic city of Karnal.
-
E.
Samalkha
Samalkha is a town in the northern Indian state of Haryana, known for its industrial activity and location along major transport routes.
- 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: Ramsthal Triple: [Bad Kissingen (district), contains, Ramsthal]
Generated description
Ramsthal is a small municipality in the Lower Franconia region of Bavaria, Germany, known for its rural character and winegrowing tradition.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ramsthal Target entity description: Ramsthal is a small municipality in the Lower Franconia region of Bavaria, Germany, known for its rural character and winegrowing tradition.
-
A.
Lothagam
Lothagam is an archaeological and geological site in northern Kenya known for its ancient human burials and prominent rock formations along the western shore of Lake Turkana.
-
B.
Gannat
Gannat is a small town in central France known for its rich paleontological heritage and traditional cultural festivals.
-
C.
Shedgum
Shedgum is a major production area within Saudi Arabia’s vast Ghawar oil field, known for its significant contribution to the country’s crude oil output.
-
D.
Gharaunda
Gharaunda is a town in the Indian state of Haryana known for its agricultural market and proximity to the historic city of Karnal.
-
E.
Samalkha
Samalkha is a town in the northern Indian state of Haryana, known for its industrial activity and location along major transport routes.
- 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_69d6aa8a6a548190a750f944ccdc8064 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d787b574d08190adec34b814a26437 |
completed | April 9, 2026, 11:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e344f95ab88190bbce8f0eab0b2713 |
completed | April 18, 2026, 8:46 a.m. |
| NEDg | Description generation | batch_69e3556e8b408190a02a1fe194ae5750 |
completed | April 18, 2026, 9:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e3591ecd548190b049ce95fe3f86d9 |
completed | April 18, 2026, 10:12 a.m. |
Created at: April 8, 2026, 9:24 p.m.