Triple
T12800586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helene Bresslau |
E306006
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Bresslau |
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: Bresslau | Statement: [Helene Bresslau, familyName, Bresslau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bresslau Context triple: [Helene Bresslau, familyName, Bresslau]
-
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.
Perasdorf
Perasdorf is a small municipality in the Straubing-Bogen district of Lower Bavaria, Germany.
-
C.
Leuchau
Leuchau is a small municipality located in the Kulmbach district of northern Bavaria, Germany.
-
D.
Reichenberg
Reichenberg is the former German name for the city of Liberec, a major urban center in the northern Czech Republic near the border with Germany and Poland.
-
E.
Biesenthal
Biesenthal is a small town in the Barnim district of Brandenburg, Germany, known for its surrounding lakes, forests, and location within the Barnim Nature Park.
- 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_69d7bdf366888190a8cccb982606889c |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e7d3f5c8190bf01bef5d263ca26 |
completed | April 10, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6850f9ae4819094599b48d8d3a074 |
completed | May 2, 2026, 11:13 p.m. |
Created at: April 9, 2026, 5:30 p.m.