Triple
T12566809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Westphalia |
E295497
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Warburg |
E516535
|
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: Warburg | Statement: [Province of Westphalia, containsSettlement, Warburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Warburg Context triple: [Province of Westphalia, containsSettlement, Warburg]
-
A.
Warburg
Warburg is a prominent German-Jewish banking and philanthropic family historically influential in international finance and economic policy.
-
B.
Warburg
chosen
Warburg is a historic small city in the German state of Hesse, known for its well-preserved medieval old town and hilltop castle.
-
C.
Landsberg
Landsberg is a town in the Saalekreis district of the German state of Saxony-Anhalt.
-
D.
Hadern
Hadern is a borough in the southwest of Munich, Germany, known for its residential character and the large Waldfriedhof cemetery.
-
E.
Westphal
Westphal is a German-origin surname borne by various notable individuals in fields such as sports, politics, and academia.
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d954a325948190994bcfc9d571a3a8 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6558f87b081909ba179b49bae3913 |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 8, 2026, 11:49 p.m.