Triple
T2025178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upper Bavaria |
E44191
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Erding
Erding is a Bavarian town northeast of Munich, best known for its historic center, Erdinger Weißbräu brewery, and large thermal spa complex.
|
E440341
|
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: Erding | Statement: [Upper Bavaria, contains, Erding]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Erding Context triple: [Upper Bavaria, contains, Erding]
-
A.
Rosenheim
Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
-
B.
Traunstein
Traunstein is a town in southeastern Bavaria, Germany, known as a regional administrative and cultural center near the Chiemsee and the Alps.
-
C.
Gauting
Gauting is a municipality in the district of Starnberg in Bavaria, Germany, known for its residential character and proximity to Munich.
-
D.
Forchheim
Forchheim is a town in Upper Franconia, Bavaria, Germany, known for its historic old town and location along major regional rail and road routes.
-
E.
Straubing
Straubing is a Bavarian town on the Danube River known for its historic city center and role as a regional economic and educational 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: Erding Triple: [Upper Bavaria, contains, Erding]
Generated description
Erding is a Bavarian town northeast of Munich, best known for its historic center, Erdinger Weißbräu brewery, and large thermal spa complex.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Erding Target entity description: Erding is a Bavarian town northeast of Munich, best known for its historic center, Erdinger Weißbräu brewery, and large thermal spa complex.
-
A.
Rosenheim
Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
-
B.
Traunstein
Traunstein is a town in southeastern Bavaria, Germany, known as a regional administrative and cultural center near the Chiemsee and the Alps.
-
C.
Gauting
Gauting is a municipality in the district of Starnberg in Bavaria, Germany, known for its residential character and proximity to Munich.
-
D.
Forchheim
Forchheim is a town in Upper Franconia, Bavaria, Germany, known for its historic old town and location along major regional rail and road routes.
-
E.
Straubing
Straubing is a Bavarian town on the Danube River known for its historic city center and role as a regional economic and educational 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_69a8891201bc8190aca837be6de41579 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb8f3faa08190a48ae1355d6e009f |
completed | March 7, 2026, 5:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6130aaa7081908956e2db62005b92 |
completed | March 15, 2026, 2:01 a.m. |
| NEDg | Description generation | batch_69b613f0d5dc8190a48e60c63ea9d717 |
completed | March 15, 2026, 2:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b617f70f608190bce1043c2254c9e5 |
completed | March 15, 2026, 2:22 a.m. |
Created at: March 4, 2026, 7:38 p.m.