Triple
T1176322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess Augusta of Saxe-Gotha |
E25033
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Gotha |
E258439
|
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: Gotha | Statement: [Princess Augusta of Saxe-Gotha, placeOfBirth, Gotha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gotha Context triple: [Princess Augusta of Saxe-Gotha, placeOfBirth, Gotha]
-
A.
Gotha
chosen
Gotha is a historic German city in Thuringia known for its former ducal court, cultural heritage, and role as a residence of various German noble houses.
-
B.
Eisenach
Eisenach is a historic town in central Germany best known for its associations with Martin Luther and as the birthplace of composer Johann Sebastian Bach.
-
C.
Jena
Jena is a historic university city in the German state of Thuringia, known for its role in optics, philosophy, and science.
-
D.
Coburg
Coburg is a historic town in northern Bavaria, Germany, known for its well-preserved medieval architecture and its former role as the seat of the Duchy of Saxe-Coburg and Gotha.
-
E.
Oranienburg
Oranienburg is a town in Brandenburg, Germany, historically known as the site of the Nazi Sachsenhausen concentration camp.
- 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_69a494267b4c819088c97a59182bf56a |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd0d5c288190b597dae0fbe3b43b |
completed | March 1, 2026, 10:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af2b3a21248190aca7710ae6ad6478 |
completed | March 9, 2026, 8:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.