Triple
T10071104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wadowice County |
E213628
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Lanckorona
Lanckorona is a historic village in southern Poland known for its well-preserved wooden architecture and picturesque hillside setting.
|
E839337
|
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: Lanckorona | Statement: [Wadowice County, containsSettlement, Lanckorona]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lanckorona Context triple: [Wadowice County, containsSettlement, Lanckorona]
-
A.
Lichmera
Lichmera is a genus of honeyeaters, small nectar-feeding passerine birds native mainly to Australasia and surrounding regions.
-
B.
Karwia
Karwia is a seaside village on the Baltic coast of northern Poland, known for its wide sandy beaches and role as a popular summer resort.
-
C.
Lanaken
Lanaken is a municipality in the Belgian province of Limburg, known for its proximity to Maastricht and its mix of residential areas, industry, and natural landscapes.
-
D.
Tarnos
Tarnos is a commune in southwestern France’s Landes department, known for its Atlantic coastline and proximity to the cities of Bayonne and Anglet.
-
E.
Horki
Horki is a town in eastern Belarus known for its agricultural academy and regional administrative significance.
- 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: Lanckorona Triple: [Wadowice County, containsSettlement, Lanckorona]
Generated description
Lanckorona is a historic village in southern Poland known for its well-preserved wooden architecture and picturesque hillside setting.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lanckorona Target entity description: Lanckorona is a historic village in southern Poland known for its well-preserved wooden architecture and picturesque hillside setting.
-
A.
Lichmera
Lichmera is a genus of honeyeaters, small nectar-feeding passerine birds native mainly to Australasia and surrounding regions.
-
B.
Karwia
Karwia is a seaside village on the Baltic coast of northern Poland, known for its wide sandy beaches and role as a popular summer resort.
-
C.
Lanaken
Lanaken is a municipality in the Belgian province of Limburg, known for its proximity to Maastricht and its mix of residential areas, industry, and natural landscapes.
-
D.
Tarnos
Tarnos is a commune in southwestern France’s Landes department, known for its Atlantic coastline and proximity to the cities of Bayonne and Anglet.
-
E.
Horki
Horki is a town in eastern Belarus known for its agricultural academy and regional administrative significance.
- 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_69ca839add308190b57d53b4ec21f2d0 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd01279388190b94c8def00425c78 |
completed | April 2, 2026, 2:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d29aaa61308190b134b49a6c1c1131 |
completed | April 5, 2026, 5:23 p.m. |
| NEDg | Description generation | batch_69d29e8617c08190bf4fb02ac40caba3 |
completed | April 5, 2026, 5:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d29f20b2f48190906d7e53fb1e5544 |
completed | April 5, 2026, 5:42 p.m. |
Created at: March 30, 2026, 8:59 p.m.