Triple
T19253943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | House of Saxe-Hildburghausen |
E481465
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Hildburghausen |
—
|
NE NERFINISHED |
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: Hildburghausen | Statement: [House of Saxe-Hildburghausen, capital, Hildburghausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hildburghausen Context triple: [House of Saxe-Hildburghausen, capital, Hildburghausen]
-
A.
Hildburghausen
chosen
Hildburghausen is a town in the German state of Thuringia that historically served as the residence of the dukes of Saxe-Hildburghausen.
-
B.
Gräfenhausen
Gräfenhausen is a district of the town of Weiterstadt in the state of Hesse, Germany.
-
C.
Wittighausen
Wittighausen is a small municipality in the Main-Tauber district of Baden-Württemberg in southern Germany.
-
D.
Haßfurt
Haßfurt is a small town in northern Bavaria, Germany, situated on the Main River and known for its historic architecture and regional administrative role.
-
E.
Rudolstadt
Rudolstadt is a historic town in the German state of Thuringia, known for its picturesque old town, Heidecksburg Castle, and cultural festivals.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8cd9d1081908a181d02b88b59b8 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fb3339648190a87d38ce42aff016 |
completed | April 20, 2026, 10:08 a.m. |
Created at: April 10, 2026, 1:28 p.m.