Triple
T13358075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vallendar |
E318745
|
entity |
| Predicate | locatedOpposite |
P3232
|
FINISHED |
| Object |
Bendorf
Bendorf is a town on the Rhine River in Rhineland-Palatinate, Germany, known for its industrial heritage and proximity to Koblenz.
|
E1051019
|
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: Bendorf | Statement: [Vallendar, locatedOpposite, Bendorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bendorf Context triple: [Vallendar, locatedOpposite, Bendorf]
-
A.
Waltershof
Waltershof is an industrial and port district of Hamburg, Germany, located within the borough of Hamburg-Mitte.
-
B.
Frenkendorf
Frenkendorf is a municipality in the canton of Basel-Landschaft in northwestern Switzerland, located near the city of Basel.
-
C.
Antdorf
Antdorf is a small rural municipality in Upper Bavaria, Germany, known for its traditional Bavarian character and scenic Alpine foothill landscape.
-
D.
Obergoms
Obergoms is a municipality in the canton of Valais in southwestern Switzerland, known for its high Alpine landscapes and traditional mountain villages.
-
E.
Rugendorf
Rugendorf is a small municipality in the Bavarian region of Upper Franconia in Germany.
- 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: Bendorf Triple: [Vallendar, locatedOpposite, Bendorf]
Generated description
Bendorf is a town on the Rhine River in Rhineland-Palatinate, Germany, known for its industrial heritage and proximity to Koblenz.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bendorf Target entity description: Bendorf is a town on the Rhine River in Rhineland-Palatinate, Germany, known for its industrial heritage and proximity to Koblenz.
-
A.
Waltershof
Waltershof is an industrial and port district of Hamburg, Germany, located within the borough of Hamburg-Mitte.
-
B.
Frenkendorf
Frenkendorf is a municipality in the canton of Basel-Landschaft in northwestern Switzerland, located near the city of Basel.
-
C.
Antdorf
Antdorf is a small rural municipality in Upper Bavaria, Germany, known for its traditional Bavarian character and scenic Alpine foothill landscape.
-
D.
Obergoms
Obergoms is a municipality in the canton of Valais in southwestern Switzerland, known for its high Alpine landscapes and traditional mountain villages.
-
E.
Rugendorf
Rugendorf is a small municipality in the Bavarian region of Upper Franconia in Germany.
- 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_69d806b7bbac8190b85278c87fa7aff3 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69da62887e588190bd7241c720a112a2 |
completed | April 11, 2026, 3:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f77f7a13508190bbab6eb68fb52a18 |
completed | May 3, 2026, 5:01 p.m. |
| NEDg | Description generation | batch_69f78058d4c88190be75e0a38cdc20da |
completed | May 3, 2026, 5:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f78157b9cc8190a1855cb9715aa7d5 |
completed | May 3, 2026, 5:09 p.m. |
Created at: April 9, 2026, 9:32 p.m.