Triple
T2467588
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chemnitz–Aue railway |
E55288
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Aue |
E270060
|
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: Aue | Statement: [Chemnitz–Aue railway, connects, Aue]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aue Context triple: [Chemnitz–Aue railway, connects, Aue]
-
A.
Aue
chosen
Aue is a town in the Ore Mountains region of Saxony, Germany, known historically for its mining industry and role as a local transport hub.
-
B.
Valleiry
Valleiry is a small French commune in the Haute-Savoie department of the Auvergne-Rhône-Alpes region in southeastern France, near the Swiss border.
-
C.
Huelén
Huelén is the former indigenous name for Cerro Santa Lucía, a historic hill and urban park in central Santiago, Chile.
-
D.
Mauregard
Mauregard is a small commune in the Seine-et-Marne department of the Île-de-France region in north-central France, situated near Paris Charles de Gaulle Airport.
-
E.
Arona
Arona is a coastal tourist municipality in southern Tenerife, Spain, known for its popular beach resorts such as Los Cristianos and Playa de las Américas.
- 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_69ab49e3622c8190ad22afa2c4fbb807 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd13310a8819095fd70672f933aa3 |
completed | March 7, 2026, 7:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af1f86a1bc8190af02a1109ccf0773 |
completed | March 9, 2026, 7:29 p.m. |
Created at: March 6, 2026, 9:44 p.m.