Triple
T2973772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Breslau |
E80345
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Breslau |
E238097
|
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: Breslau | Statement: [University of Breslau, locatedIn, Breslau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Breslau Context triple: [University of Breslau, locatedIn, Breslau]
-
A.
Breslau
chosen
Breslau is the historical German name for the city now known as Wrocław in southwestern Poland, a major cultural and academic center in Central Europe.
-
B.
Oppeln
Oppeln is the historical German name for the city of Opole, a major cultural and administrative center in southwestern Poland’s Silesia region.
-
C.
Frankfurt (Oder)
Frankfurt (Oder) is a German city on the Oder River at the Polish border, known as a historic university and trade center in the state of Brandenburg.
-
D.
Cieszyn
Cieszyn is a historic town in southern Poland on the Olza River, known for its shared Polish-Czech heritage and well-preserved old town.
-
E.
Dresden
Dresden is a small community within the municipality of Chatham-Kent in southwestern Ontario, Canada, known historically for its role in the Underground Railroad and Black settlement.
- 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_69ad8b14ffe881908ffed62f9595c867 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9987bb6c8190adfb447b76276962 |
completed | March 8, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2358bd4cc81908970e1d3cdc95b5d |
completed | March 12, 2026, 3:39 a.m. |
Created at: March 8, 2026, 2:58 p.m.