Triple
T11475320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | House of Ascania |
E272011
|
entity |
| Predicate | hasMainTerritory |
P1103
|
FINISHED |
| Object | Ballendstedt |
E862763
|
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: Ballendstedt | Statement: [House of Ascania, hasMainTerritory, Ballendstedt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ballendstedt Context triple: [House of Ascania, hasMainTerritory, Ballendstedt]
-
A.
Ballenstedt
chosen
Ballenstedt is a historic town in the German state of Saxony-Anhalt, known for its castle and location on the northern edge of the Harz Mountains.
-
B.
Hettstedt
Hettstedt is a small German town in the state of Saxony-Anhalt, historically known for its copper mining and metalworking industry.
-
C.
Stedesdorf
Stedesdorf is a small municipality in Lower Saxony, Germany, situated in the East Frisian region.
-
D.
Elsterwerda
Elsterwerda is a small town in the state of Brandenburg in eastern Germany, known for its regional railway connections and location near the Elbe-Elster district.
-
E.
Augustdorf
Augustdorf is a municipality in North Rhine-Westphalia, Germany, known for its proximity to the Teutoburg Forest and its significant military presence, including Bundeswehr facilities.
- 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_69d6aae0c8d881908a5a360c0be3242e |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8294c8dc48190a515f83c99405a3b |
completed | April 9, 2026, 10:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f49c7ab48c8190a7cf4e6be6aacc12 |
completed | May 1, 2026, 12:28 p.m. |
Created at: April 8, 2026, 9:36 p.m.