Triple
T11222071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rottal-Inn |
E265593
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Falkenberg
Falkenberg is a small municipality in the Rottal-Inn district of Lower Bavaria in southeastern Germany.
|
E924042
|
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: Falkenberg | Statement: [Rottal-Inn, contains, Falkenberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Falkenberg Context triple: [Rottal-Inn, contains, Falkenberg]
-
A.
Falkenberg
Falkenberg is a coastal town in southwestern Sweden known for its beaches, fishing heritage, and location along the River Ätran.
-
B.
Falkenberg
Falkenberg is a locality in the borough of Lichtenberg in Berlin, Germany, known for its more rural character on the city's northeastern edge.
-
C.
Falköping
Falköping is a small Swedish town known for its surrounding ancient burial mounds, rolling agricultural landscape, and location between the plateaus of Mösseberg and Ålleberg.
-
D.
Fagersta
Fagersta is an industrial town in central Sweden known for its steel production and manufacturing heritage.
-
E.
Bengtsfors
Bengtsfors is a small town in western Sweden known for its lakeside setting, forests, and role as a local administrative and service center.
- 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: Falkenberg Triple: [Rottal-Inn, contains, Falkenberg]
Generated description
Falkenberg is a small municipality in the Rottal-Inn district of Lower Bavaria in southeastern Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Falkenberg Target entity description: Falkenberg is a small municipality in the Rottal-Inn district of Lower Bavaria in southeastern Germany.
-
A.
Falkenberg
Falkenberg is a coastal town in southwestern Sweden known for its beaches, fishing heritage, and location along the River Ätran.
-
B.
Falkenberg
Falkenberg is a locality in the borough of Lichtenberg in Berlin, Germany, known for its more rural character on the city's northeastern edge.
-
C.
Falköping
Falköping is a small Swedish town known for its surrounding ancient burial mounds, rolling agricultural landscape, and location between the plateaus of Mösseberg and Ålleberg.
-
D.
Fagersta
Fagersta is an industrial town in central Sweden known for its steel production and manufacturing heritage.
-
E.
Bengtsfors
Bengtsfors is a small town in western Sweden known for its lakeside setting, forests, and role as a local administrative and service center.
- 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_69d6aac59460819089b9848b27f57848 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8ec8fb08190b27144ab65f85957 |
completed | April 9, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5b795f7948190a0dd53e8e034fe58 |
completed | April 20, 2026, 5:20 a.m. |
| NEDg | Description generation | batch_69e5bb5d6e0c8190933cd3d6e83c24a2 |
completed | April 20, 2026, 5:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e5c29d7b608190ae79bb8318211547 |
completed | April 20, 2026, 6:07 a.m. |
Created at: April 8, 2026, 9:30 p.m.