Triple
T15539127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aš |
E370428
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object |
Selb
Selb is a town in northeastern Bavaria, Germany, known for its porcelain industry and location near the Czech border.
|
E1162184
|
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: Selb | Statement: [Aš, twinTown, Selb]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Selb Context triple: [Aš, twinTown, Selb]
-
A.
Zwiesel
Zwiesel is a small Bavarian town in southeastern Germany known for its glassmaking tradition and its location on the edge of the Bavarian Forest.
-
B.
Zwiesel
Zwiesel is a prominent mountain in the Bavarian Alps of southeastern Germany, known for its scenic hiking routes and panoramic views over the Bad Reichenhall area.
-
C.
Starnberg
Starnberg is a lakeside town in Bavaria, Germany, known for its affluent residential character and scenic location on Lake Starnberg southwest of Munich.
-
D.
Saalfeld
Saalfeld is a town in the German state of Thuringia, known for its historic old town and former significance as a regional railway and industrial center.
-
E.
Backnang
Backnang is a town in the German state of Baden-Württemberg, located northeast of Stuttgart and known for its historical center and role as a regional industrial and commuter hub.
- 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: Selb Triple: [Aš, twinTown, Selb]
Generated description
Selb is a town in northeastern Bavaria, Germany, known for its porcelain industry and location near the Czech border.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Selb Target entity description: Selb is a town in northeastern Bavaria, Germany, known for its porcelain industry and location near the Czech border.
-
A.
Zwiesel
Zwiesel is a small Bavarian town in southeastern Germany known for its glassmaking tradition and its location on the edge of the Bavarian Forest.
-
B.
Zwiesel
Zwiesel is a prominent mountain in the Bavarian Alps of southeastern Germany, known for its scenic hiking routes and panoramic views over the Bad Reichenhall area.
-
C.
Starnberg
Starnberg is a lakeside town in Bavaria, Germany, known for its affluent residential character and scenic location on Lake Starnberg southwest of Munich.
-
D.
Saalfeld
Saalfeld is a town in the German state of Thuringia, known for its historic old town and former significance as a regional railway and industrial center.
-
E.
Backnang
Backnang is a town in the German state of Baden-Württemberg, located northeast of Stuttgart and known for its historical center and role as a regional industrial and commuter hub.
- 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04430b5188190a555a3cd4fb0c61c |
completed | April 16, 2026, 2:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d626e688190bd93481cfd6cb255 |
completed | May 9, 2026, 1:57 p.m. |
| NEDg | Description generation | batch_69ff3f075bb881908c254137ca7c3f9f |
completed | May 9, 2026, 2:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff3f87f788819080eccae52b0df145 |
completed | May 9, 2026, 2:07 p.m. |
Created at: April 10, 2026, 4:07 a.m.