Triple
T21036141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Halle (Saale) region |
E518193
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Kabelsketal |
—
|
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: Kabelsketal | Statement: [Halle (Saale) region, contains, Kabelsketal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kabelsketal Context triple: [Halle (Saale) region, contains, Kabelsketal]
-
A.
Kabelsketal
chosen
Kabelsketal is a municipality in the Saalekreis district of Saxony-Anhalt in central Germany, situated near the city of Halle (Saale).
-
B.
Kabelvåg
Kabelvåg is a historic fishing village and tourist destination in the Lofoten archipelago of northern Norway, known for its coastal scenery and traditional architecture.
-
C.
Kabarnet
Kabarnet is a town in Kenya that serves as an administrative and commercial center in the Rift Valley region.
-
D.
Kettenis
Kettenis is a village and municipal section of the city of Eupen in the German-speaking Community of eastern Belgium.
-
E.
Kablar
Kablar is a prominent mountain in central Serbia, known for its scenic views over the West Morava River and proximity to the city of Čačak.
- 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_69e0b503275c8190afd9a163f997c709 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc865ca88190abf336ee9012fa77 |
completed | April 21, 2026, 4:26 a.m. |
Created at: April 16, 2026, 2:02 p.m.