Triple
T2487681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chemnitz–Riesa railway |
E55963
|
entity |
| Predicate | hasEndpointCity |
P26386
|
FINISHED |
| Object | Chemnitz |
E1679
|
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: Chemnitz | Statement: [Chemnitz–Riesa railway, hasEndpointCity, Chemnitz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chemnitz Context triple: [Chemnitz–Riesa railway, hasEndpointCity, Chemnitz]
-
A.
Chemnitz
chosen
Chemnitz is a city in eastern Germany known for its industrial heritage and post-reunification urban redevelopment.
-
B.
Zwickau
Zwickau is a city in the German state of Saxony known historically as an important center of the automotive industry and as the birthplace of composer Robert Schumann.
-
C.
Dresden
Dresden is a small community within the municipality of Chatham-Kent in southwestern Ontario, Canada, known historically for its role in the Underground Railroad and Black settlement.
-
D.
Dresden
Dresden is a historic cultural and economic center in eastern Germany, renowned for its baroque architecture, art collections, and reconstruction after World War II.
-
E.
Cottbus
Cottbus is a city in eastern Germany known as a regional center for science and technology, including aerospace research.
- 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_69ab49e670a88190b928e08302381710 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd1782ca081909645164a6acf0ea0 |
completed | March 7, 2026, 7:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b56b217af0819084d8aed695b8377b |
completed | March 14, 2026, 2:05 p.m. |
Created at: March 6, 2026, 9:45 p.m.