Triple
T3710497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oskar Schindler |
E81398
|
entity |
| Predicate | residence |
P75
|
FINISHED |
| Object | Brünnlitz |
E383744
|
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: Brünnlitz | Statement: [Oskar Schindler, residence, Brünnlitz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brünnlitz Context triple: [Oskar Schindler, residence, Brünnlitz]
-
A.
Brünnlitz
chosen
Brünnlitz is a village in the Czech Republic best known as the location of Oskar Schindler’s wartime factory where he employed and saved Jewish workers during the Holocaust.
-
B.
Olbernhau
Olbernhau is a town in Germany’s Ore Mountains renowned for its traditional woodcraft industry, especially the production of Schwibbogen candle arches and other Christmas decorations.
-
C.
Zwönitz
Zwönitz is a river in Saxony, Germany, that serves as one of the headstreams of the Chemnitz River.
-
D.
Dinkelsbühl
Dinkelsbühl is a well-preserved medieval town in Bavaria, Germany, renowned for its intact city walls, historic half-timbered houses, and picturesque old town.
-
E.
Tirschenreuth
Tirschenreuth is a town in northeastern Bavaria, Germany, known for its historic town center and surrounding lake and pond landscapes.
- 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_69ad8b1a81588190b3f27a5483bb610e |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adc584b86c8190ba1a1073da440b07 |
completed | March 8, 2026, 6:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4e4ed47a88190ab5414b7618e7e9c |
completed | March 14, 2026, 4:32 a.m. |
Created at: March 8, 2026, 3:33 p.m.