Triple
T15757592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Innerste |
E382006
|
entity |
| Predicate | hasTributary |
P415
|
FINISHED |
| Object | Nette |
E379323
|
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: Nette | Statement: [Innerste, hasTributary, Nette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nette Context triple: [Innerste, hasTributary, Nette]
-
A.
Nette
chosen
Nette is a river in Germany that serves as a tributary of the Innerste.
-
B.
Libná
Libná is a small settlement that forms part of the town of Teplice nad Metují in the Hradec Králové Region of the Czech Republic.
-
C.
Blatná
Blatná is a historic Czech town best known for its picturesque water castle and surrounding ponds in the South Bohemian countryside.
-
D.
Třemešné
Třemešné is a small municipality and village in the Plzeň Region of the Czech Republic.
-
E.
Novotný
Novotný is a common Czech surname borne by various notable figures in politics, arts, and sports.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b1ff4881909d5240d1d30f5c8b |
completed | April 16, 2026, 3 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff877311dc8190b55fe7ca5c0843da |
completed | May 9, 2026, 7:13 p.m. |
Created at: April 10, 2026, 4:47 a.m.