Triple
T17835756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hugo Schmeisser |
E445378
|
entity |
| Predicate | residence |
P75
|
FINISHED |
| Object | Suhl |
—
|
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: Suhl | Statement: [Hugo Schmeisser, residence, Suhl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Suhl Context triple: [Hugo Schmeisser, residence, Suhl]
-
A.
Suhl
chosen
Suhl is a city in central Germany known historically as a center of firearms manufacturing and located in the federal state of Thuringia.
-
B.
Gelnhausen
Gelnhausen is a historic town in the German state of Hesse, known for its well-preserved medieval architecture and former status as a Free Imperial City of the Holy Roman Empire.
-
C.
Melsungen
Melsungen is a small historic town in northern Hesse, Germany, known for its well-preserved half-timbered houses and picturesque setting on the Fulda River.
-
D.
Borgholzhausen
Borgholzhausen is a small town in North Rhine-Westphalia, Germany, known for its location on the Teutoburg Forest and its historical ties to the former County of Ravensberg.
-
E.
Filderstadt
Filderstadt is a town in the German state of Baden-Württemberg, situated just south of Stuttgart and known for its proximity to Stuttgart Airport and role as a regional transport hub.
- 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_69d8b9f1a6d881909f024bc603111cdb |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48d27f8908190bf48a8153756effa |
completed | April 19, 2026, 8:07 a.m. |
Created at: April 10, 2026, 10:16 a.m.