Triple
T14314346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Limmattal |
E354914
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object |
Knonaueramt
Knonaueramt is a district in the canton of Zurich, Switzerland, known for its rural character, small towns, and location between the Albis hills and the Reuss river.
|
E1093945
|
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: Knonaueramt | Statement: [Limmattal, borders, Knonaueramt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Knonaueramt Context triple: [Limmattal, borders, Knonaueramt]
-
A.
Kaltenborn
Kaltenborn is a small municipality in the Ahrweiler district of Rhineland-Palatinate, western Germany, situated in the Eifel region.
-
B.
Kallenbach
Kallenbach is a German-language surname most notably borne by Hermann Kallenbach, a close associate of Mahatma Gandhi.
-
C.
Biesenthal
Biesenthal is a small town in the Barnim district of Brandenburg, Germany, known for its surrounding lakes, forests, and location within the Barnim Nature Park.
-
D.
Spangenberg
Spangenberg is a small town in Germany, historically situated within the region of Westphalia.
-
E.
Muffendorf
Muffendorf is a historic, village-like residential quarter in the Bonn district of Bad Godesberg, known for its traditional half-timbered houses and picturesque setting.
- 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: Knonaueramt Triple: [Limmattal, borders, Knonaueramt]
Generated description
Knonaueramt is a district in the canton of Zurich, Switzerland, known for its rural character, small towns, and location between the Albis hills and the Reuss river.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Knonaueramt Target entity description: Knonaueramt is a district in the canton of Zurich, Switzerland, known for its rural character, small towns, and location between the Albis hills and the Reuss river.
-
A.
Kaltenborn
Kaltenborn is a small municipality in the Ahrweiler district of Rhineland-Palatinate, western Germany, situated in the Eifel region.
-
B.
Kallenbach
Kallenbach is a German-language surname most notably borne by Hermann Kallenbach, a close associate of Mahatma Gandhi.
-
C.
Biesenthal
Biesenthal is a small town in the Barnim district of Brandenburg, Germany, known for its surrounding lakes, forests, and location within the Barnim Nature Park.
-
D.
Spangenberg
Spangenberg is a small town in Germany, historically situated within the region of Westphalia.
-
E.
Muffendorf
Muffendorf is a historic, village-like residential quarter in the Bonn district of Bad Godesberg, known for its traditional half-timbered houses and picturesque setting.
- 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_69d8278ed42c8190b9f882dcce611347 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de85b49e5481909b9ffab2d922e284 |
completed | April 14, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4687c6bc819088452892128c420e |
completed | May 8, 2026, 2:12 a.m. |
| NEDg | Description generation | batch_69fd47e2b8d481909ed8274a96615b36 |
completed | May 8, 2026, 2:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd4879b2688190ac208545ae226c93 |
completed | May 8, 2026, 2:20 a.m. |
Created at: April 10, 2026, 1:12 a.m.