Triple
T2019050
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toruń |
E44061
|
entity |
| Predicate | hasSportsTeam |
P330
|
FINISHED |
| Object |
Elana Toruń
Elana Toruń is a Polish football club based in the city of Toruń.
|
E227834
|
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: Elana Toruń | Statement: [Toruń, hasSportsTeam, Elana Toruń]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elana Toruń Context triple: [Toruń, hasSportsTeam, Elana Toruń]
-
A.
Aleksandra Dulkiewicz
Aleksandra Dulkiewicz is a Polish lawyer and politician who serves as the mayor of Gdańsk, known for her pro-European stance and advocacy of democratic values.
-
B.
Ewelina Hańska
Ewelina Hańska was a Polish noblewoman best known as the longtime correspondent, muse, and eventually wife of French novelist Honoré de Balzac.
-
C.
Monika Lenczewska
Monika Lenczewska is a Polish cinematographer known for her visually striking work on international films and television projects.
-
D.
Tanja Stomporowski
Tanja Stomporowski is a German local politician who serves as the mayor of the town of Quakenbrück in Lower Saxony.
-
E.
Sophie Zawistowski
Sophie Zawistowski is the tragic Polish Holocaust survivor at the center of William Styron’s novel and its film adaptation, whose harrowing past and impossible moral dilemma define the story’s emotional core.
- 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: Elana Toruń Triple: [Toruń, hasSportsTeam, Elana Toruń]
Generated description
Elana Toruń is a Polish football club based in the city of Toruń.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Elana Toruń Target entity description: Elana Toruń is a Polish football club based in the city of Toruń.
-
A.
Aleksandra Dulkiewicz
Aleksandra Dulkiewicz is a Polish lawyer and politician who serves as the mayor of Gdańsk, known for her pro-European stance and advocacy of democratic values.
-
B.
Ewelina Hańska
Ewelina Hańska was a Polish noblewoman best known as the longtime correspondent, muse, and eventually wife of French novelist Honoré de Balzac.
-
C.
Monika Lenczewska
Monika Lenczewska is a Polish cinematographer known for her visually striking work on international films and television projects.
-
D.
Tanja Stomporowski
Tanja Stomporowski is a German local politician who serves as the mayor of the town of Quakenbrück in Lower Saxony.
-
E.
Sophie Zawistowski
Sophie Zawistowski is the tragic Polish Holocaust survivor at the center of William Styron’s novel and its film adaptation, whose harrowing past and impossible moral dilemma define the story’s emotional core.
- 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_69abb8cfa5c88190b55bce5db968665b |
completed | March 7, 2026, 5:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae1fe88e8881909f2e64ebe23b6d1f |
completed | March 9, 2026, 1:18 a.m. |
| NEDg | Description generation | batch_69ae20641b088190bdbc7c39736eb585 |
completed | March 9, 2026, 1:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae20e214a88190b85432b9e47cde12 |
completed | March 9, 2026, 1:22 a.m. |
Created at: March 4, 2026, 7:38 p.m.