Triple
T8797642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taunusstein |
E209327
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Orlen
Orlen is a district of the town of Taunusstein in the Rheingau-Taunus-Kreis region of Hesse, Germany.
|
E759643
|
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: Orlen | Statement: [Taunusstein, hasSubdivision, Orlen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orlen Context triple: [Taunusstein, hasSubdivision, Orlen]
-
A.
Łódź Fabryczna
Łódź Fabryczna is a major modern railway terminus in Łódź, Poland, serving as one of the city’s primary long-distance and regional train hubs.
-
B.
Kujawiak
Kujawiak is a traditional Polish folk dance from the Kuyavia region, characterized by its slow, lyrical tempo and smooth, gliding movements.
-
C.
Energetica
Energetica is an interactive exhibition at Amsterdam’s NEMO Science Museum that explores the principles and applications of sustainable energy and natural forces.
-
D.
UPC Polska
UPC Polska is a leading Polish telecommunications company that provides broadband internet, digital television, and telephone services to households and businesses across Poland.
-
E.
KGHM Polska Miedź
KGHM Polska Miedź is a major Polish state-controlled mining and metallurgy company, and one of the world’s leading producers of copper and silver.
- 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: Orlen Triple: [Taunusstein, hasSubdivision, Orlen]
Generated description
Orlen is a district of the town of Taunusstein in the Rheingau-Taunus-Kreis region of Hesse, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Orlen Target entity description: Orlen is a district of the town of Taunusstein in the Rheingau-Taunus-Kreis region of Hesse, Germany.
-
A.
Łódź Fabryczna
Łódź Fabryczna is a major modern railway terminus in Łódź, Poland, serving as one of the city’s primary long-distance and regional train hubs.
-
B.
Kujawiak
Kujawiak is a traditional Polish folk dance from the Kuyavia region, characterized by its slow, lyrical tempo and smooth, gliding movements.
-
C.
Energetica
Energetica is an interactive exhibition at Amsterdam’s NEMO Science Museum that explores the principles and applications of sustainable energy and natural forces.
-
D.
UPC Polska
UPC Polska is a leading Polish telecommunications company that provides broadband internet, digital television, and telephone services to households and businesses across Poland.
-
E.
KGHM Polska Miedź
KGHM Polska Miedź is a major Polish state-controlled mining and metallurgy company, and one of the world’s leading producers of copper and silver.
- 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_69ca836240888190a62b262e56a69d2f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5fa370d08190885ef65e3a3e56d3 |
completed | March 31, 2026, 11:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf6f5d655881909013ac3e2ac0cebb |
completed | April 3, 2026, 7:42 a.m. |
| NEDg | Description generation | batch_69cf71c118848190a937ecf714556ef3 |
completed | April 3, 2026, 7:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cf744b17e88190b14607e6dff823a3 |
completed | April 3, 2026, 8:03 a.m. |
Created at: March 30, 2026, 6:44 p.m.