Triple
T9195100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tarnobrzeg |
E220684
|
entity |
| Predicate | hasSportsClub |
P346
|
FINISHED |
| Object |
Siarka Tarnobrzeg
Siarka Tarnobrzeg is a Polish sports club best known for its football team, based in the city of Tarnobrzeg.
|
E783332
|
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: Siarka Tarnobrzeg | Statement: [Tarnobrzeg, hasSportsClub, Siarka Tarnobrzeg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Siarka Tarnobrzeg Context triple: [Tarnobrzeg, hasSportsClub, Siarka Tarnobrzeg]
-
A.
Samborzec
Samborzec is a village and the seat of a rural administrative district in southeastern Poland’s Sandomierz County.
-
B.
Ciechocinek
Ciechocinek is a Polish spa town renowned for its historic saline graduation towers and therapeutic health resorts.
-
C.
Skawina
Skawina is a town in southern Poland near Kraków, known for its industrial facilities and role as a local economic and transport hub.
-
D.
Wiślica
Wiślica is a historic town in south-central Poland, known for its medieval architecture and archaeological significance as one of the country’s oldest settlements.
-
E.
Turośl
Turośl is a village in northern Poland located within the Warmian-Masurian Voivodeship, a region known for its lakes and forests.
- 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: Siarka Tarnobrzeg Triple: [Tarnobrzeg, hasSportsClub, Siarka Tarnobrzeg]
Generated description
Siarka Tarnobrzeg is a Polish sports club best known for its football team, based in the city of Tarnobrzeg.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Siarka Tarnobrzeg Target entity description: Siarka Tarnobrzeg is a Polish sports club best known for its football team, based in the city of Tarnobrzeg.
-
A.
Samborzec
Samborzec is a village and the seat of a rural administrative district in southeastern Poland’s Sandomierz County.
-
B.
Ciechocinek
Ciechocinek is a Polish spa town renowned for its historic saline graduation towers and therapeutic health resorts.
-
C.
Skawina
Skawina is a town in southern Poland near Kraków, known for its industrial facilities and role as a local economic and transport hub.
-
D.
Wiślica
Wiślica is a historic town in south-central Poland, known for its medieval architecture and archaeological significance as one of the country’s oldest settlements.
-
E.
Turośl
Turośl is a village in northern Poland located within the Warmian-Masurian Voivodeship, a region known for its lakes and forests.
- 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_69ca83e7ba70819088b74866d9da2c30 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd87c3a3c8190b60f19873ef6e1f8 |
completed | April 1, 2026, 8:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d05c313004819090fe0e5d4e7bc15e |
completed | April 4, 2026, 12:32 a.m. |
| NEDg | Description generation | batch_69d05d138c288190a0eab9be6bd649c0 |
completed | April 4, 2026, 12:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d05df1a0888190a2bdc48a159b865e |
completed | April 4, 2026, 12:40 a.m. |
Created at: March 30, 2026, 7:25 p.m.