Triple
T10848358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grosser Arber |
E256074
|
entity |
| Predicate | nearbySettlement |
P350
|
FINISHED |
| Object |
Lohberg
Lohberg is a small Bavarian village in the Bavarian Forest region of Germany, known as a gateway to outdoor activities around the Großer Arber mountain.
|
E891181
|
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: Lohberg | Statement: [Grosser Arber, nearbySettlement, Lohberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lohberg Context triple: [Grosser Arber, nearbySettlement, Lohberg]
-
A.
Lohrberg
Lohrberg is a hill in Germany’s Siebengebirge range, known for its forested slopes and scenic hiking paths overlooking the Rhine valley.
-
B.
Lofsrud
Lofsrud is a residential area and neighborhood within the Søndre Nordstrand borough of Oslo, Norway.
-
C.
Hafslund
Hafslund is a major Norwegian energy and utility company known for its role in electricity production, distribution, and related services.
-
D.
Haslum
Haslum is a suburban area in Bærum, Norway, known for its residential neighborhoods and proximity to Oslo.
-
E.
Lönnbohm
Lönnbohm is the original family name of the renowned Finnish poet and journalist Eino Leino.
- 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: Lohberg Triple: [Grosser Arber, nearbySettlement, Lohberg]
Generated description
Lohberg is a small Bavarian village in the Bavarian Forest region of Germany, known as a gateway to outdoor activities around the Großer Arber mountain.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lohberg Target entity description: Lohberg is a small Bavarian village in the Bavarian Forest region of Germany, known as a gateway to outdoor activities around the Großer Arber mountain.
-
A.
Lohrberg
Lohrberg is a hill in Germany’s Siebengebirge range, known for its forested slopes and scenic hiking paths overlooking the Rhine valley.
-
B.
Lofsrud
Lofsrud is a residential area and neighborhood within the Søndre Nordstrand borough of Oslo, Norway.
-
C.
Hafslund
Hafslund is a major Norwegian energy and utility company known for its role in electricity production, distribution, and related services.
-
D.
Haslum
Haslum is a suburban area in Bærum, Norway, known for its residential neighborhoods and proximity to Oslo.
-
E.
Lönnbohm
Lönnbohm is the original family name of the renowned Finnish poet and journalist Eino Leino.
- 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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75114ca988190a0e730131adb2df0 |
completed | April 9, 2026, 7:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dff7cc0d648190afb0ce80bac7f3dc |
completed | April 15, 2026, 8:40 p.m. |
| NEDg | Description generation | batch_69e0b498df2481908c964d53b1782774 |
completed | April 16, 2026, 10:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e11e21fc2c8190878a877ecd3b465e |
completed | April 16, 2026, 5:36 p.m. |
Created at: April 8, 2026, 9:20 p.m.