Triple
T2611922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maria Elisabeth Lämmerhirt |
E58793
|
entity |
| Predicate | placeOfDeath |
P21
|
FINISHED |
| Object | Eisenach |
E153084
|
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: Eisenach | Statement: [Maria Elisabeth Lämmerhirt, placeOfDeath, Eisenach]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eisenach Context triple: [Maria Elisabeth Lämmerhirt, placeOfDeath, Eisenach]
-
A.
Eisenach
chosen
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.
-
B.
Kronach
Kronach is a historic town in northern Bavaria, Germany, known for its well-preserved medieval old town and the imposing Rosenberg Fortress.
-
C.
Gotha
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.
-
D.
Mühlhausen
Mühlhausen is a historic town in central Germany, known for its well-preserved medieval architecture and cultural heritage.
-
E.
Schmalkalden
Schmalkalden is a historic town in the German state of Thuringia, known for its well-preserved medieval architecture and role in Reformation-era politics.
- 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_69ab4ac444dc819099614e534dd6021f |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd87c5fec8190a428b94b90265352 |
completed | March 7, 2026, 7:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5766a918081908953b6b508e4e6e0 |
completed | March 14, 2026, 2:53 p.m. |
Created at: March 6, 2026, 9:50 p.m.