Triple
T9012301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Königstein im Taunus |
E215503
|
entity |
| Predicate | hasCityDistrict |
P2709
|
FINISHED |
| Object |
Schneidhain
Schneidhain is a district of the town Königstein im Taunus in the Hochtaunus region of Hesse, Germany.
|
E773605
|
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: Schneidhain | Statement: [Königstein im Taunus, hasCityDistrict, Schneidhain]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schneidhain Context triple: [Königstein im Taunus, hasCityDistrict, Schneidhain]
-
A.
Festungsberg
Festungsberg is a prominent hill in Salzburg, Austria, best known as the site of the medieval Hohensalzburg Fortress overlooking the city.
-
B.
Bärenkopf
Bärenkopf is a mountain peak in the Austrian Alps that forms part of the Glockner Group.
-
C.
Roßhaupten
Roßhaupten is a small Bavarian municipality in southern Germany, known for its scenic location in the Allgäu region near the Alps and popular lakes.
-
D.
Fürth Hardhöhe
Fürth Hardhöhe is a station in the city of Fürth that serves as the western terminus of a line on the Nuremberg U-Bahn rapid transit system.
-
E.
Nadelhorn
Nadelhorn is a prominent 4,000-meter-class peak in the Swiss Alps, known for its sharp, needle-like summit and popular alpine climbing 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: Schneidhain Triple: [Königstein im Taunus, hasCityDistrict, Schneidhain]
Generated description
Schneidhain is a district of the town Königstein im Taunus in the Hochtaunus region of Hesse, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Schneidhain Target entity description: Schneidhain is a district of the town Königstein im Taunus in the Hochtaunus region of Hesse, Germany.
-
A.
Festungsberg
Festungsberg is a prominent hill in Salzburg, Austria, best known as the site of the medieval Hohensalzburg Fortress overlooking the city.
-
B.
Bärenkopf
Bärenkopf is a mountain peak in the Austrian Alps that forms part of the Glockner Group.
-
C.
Roßhaupten
Roßhaupten is a small Bavarian municipality in southern Germany, known for its scenic location in the Allgäu region near the Alps and popular lakes.
-
D.
Fürth Hardhöhe
Fürth Hardhöhe is a station in the city of Fürth that serves as the western terminus of a line on the Nuremberg U-Bahn rapid transit system.
-
E.
Nadelhorn
Nadelhorn is a prominent 4,000-meter-class peak in the Swiss Alps, known for its sharp, needle-like summit and popular alpine climbing 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_69ca83a2bf088190986ee7a8eb90407d |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc69f846f88190af65dfcf8bdd936a |
completed | April 1, 2026, 12:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfdba11a6481909cac624530a77ffe |
completed | April 3, 2026, 3:24 p.m. |
| NEDg | Description generation | batch_69cfdc9868fc8190addad6b87b567277 |
completed | April 3, 2026, 3:28 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfe0aafe4c81908a5b31590f6c9152 |
completed | April 3, 2026, 3:45 p.m. |
Created at: March 30, 2026, 7:06 p.m.