Triple
T3830871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nuremberg–Würzburg railway |
E91006
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Franconia |
E128786
|
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: Franconia | Statement: [Nuremberg–Würzburg railway, locatedIn, Franconia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Franconia Context triple: [Nuremberg–Würzburg railway, locatedIn, Franconia]
-
A.
Franconia
chosen
Franconia is a historical region in northern Bavaria, Germany, known for its medieval towns, rich cultural heritage, and distinct Franconian identity within the German-speaking world.
-
B.
Franconia
Franconia is a suburban community in Fairfax County, Northern Virginia, known for its residential neighborhoods and proximity to Washington, D.C.
-
C.
Swabia (Bavaria)
Swabia (Bavaria) is an administrative region in southwestern Bavaria, Germany, known for its distinct Swabian cultural heritage and mix of industrial cities and rural landscapes.
-
D.
Pfalz
Pfalz is a major wine-producing region in southwestern Germany known for its diverse vineyards and high-quality white wines.
-
E.
Bavaria
Bavaria is a historic region and federal state in southeastern Germany, known for its distinct cultural traditions, large size and population, and major cities such as Munich.
- 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_69aed960b538819096561c8ed448dec9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeeb86207c81908f40a01fe27f6a0b |
completed | March 9, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b595eea03c8190a76a4e09a6d03919 |
completed | March 14, 2026, 5:07 p.m. |
Created at: March 9, 2026, 3:17 p.m.