Triple
T855129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Głogów |
E18473
|
entity |
| Predicate | hasSportsClub |
P346
|
FINISHED |
| Object | Chrobry Głogów |
E18473
|
NE FINISHED |
How this triple was built (2 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: Chrobry Głogów | Statement: [Głogów, hasSportsClub, Chrobry Głogów]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chrobry Głogów Context triple: [Głogów, hasSportsClub, Chrobry Głogów]
-
A.
Kazimierz
Kazimierz is a historic district of Kraków known for its rich Jewish heritage, medieval architecture, and vibrant cultural life.
-
B.
Ciechocinek
Ciechocinek is a Polish spa town renowned for its historic saline graduation towers and therapeutic health resorts.
-
C.
Glogów
chosen
Glogów is a historic town in western Poland on the Oder River, known for its medieval origins and reconstructed Old Town.
-
D.
Chrzanów
Chrzanów is a town in southern Poland known for its historical architecture and role as a local industrial and administrative center.
-
E.
Cracovia
Cracovia is a historic Polish football club from Kraków, known as one of the oldest and most traditional teams in the country.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a4938bdd3c8190a954a3c11844d9cf |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac3a48c08190b4677d825fcbfaf9 |
completed | March 1, 2026, 9:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7a3bfcf308190b1ffc63ccd32cc66 |
completed | March 4, 2026, 3:15 a.m. |
Created at: March 1, 2026, 7:39 p.m.