Triple
T855097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Głogów |
E18473
|
entity |
| Predicate | hasGermanName |
P1435
|
FINISHED |
| Object | Glogau |
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: Glogau | Statement: [Głogów, hasGermanName, Glogau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Glogau Context triple: [Głogów, hasGermanName, Glogau]
-
A.
Görlitz
Görlitz is a historic city in eastern Germany on the Lusatian Neisse River, known for its well-preserved old town and role as a popular film location.
-
B.
Tarnów
Tarnów is a historic city in southern Poland known for its well-preserved Old Town, Renaissance architecture, and cultural heritage.
-
C.
Wadowice
Wadowice is a historic town in southern Poland best known as the birthplace of Pope John Paul II.
-
D.
Glogów
chosen
Glogów is a historic town in western Poland on the Oder River, known for its medieval origins and reconstructed Old Town.
-
E.
Cieszyn Silesia
Cieszyn Silesia is a historical and ethnically diverse borderland region centered around the city of Cieszyn, spanning areas of present-day Poland and the Czech Republic.
- 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_69acd46627dc81908565f4f93cd35012 |
completed | March 8, 2026, 1:44 a.m. |
Created at: March 1, 2026, 7:39 p.m.