Triple
T11439595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aue-Bad Schlema |
E271106
|
entity |
| Predicate | hasPart |
P35
|
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: [Aue-Bad Schlema, hasPart, Aue]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aue Context triple: [Aue-Bad Schlema, hasPart, 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.
Radaur
Radaur is a town in the Yamunanagar district of Haryana, India, known primarily as a local commercial and educational center for surrounding rural areas.
-
C.
Mauguio
Mauguio is a commune in southern France near Montpellier, known for its proximity to the Mediterranean coast and its role as a local economic and transport hub.
-
D.
Aulnat
Aulnat is a commune in central France situated in the Puy-de-Dôme department within the Auvergne region.
-
E.
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.
- 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_69d6aadeef688190874bcecd88b3dd9b |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d80888190c8190b6365550ffe4931c |
completed | April 9, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5d39554c48190969cc0ebd4dbc368 |
completed | April 20, 2026, 7:19 a.m. |
Created at: April 8, 2026, 9:35 p.m.