Triple
T1890156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dnieper |
E41855
|
entity |
| Predicate | hasTributary |
P415
|
FINISHED |
| Object | Inhulets |
E112034
|
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: Inhulets | Statement: [Dnieper, hasTributary, Inhulets]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Inhulets Context triple: [Dnieper, hasTributary, Inhulets]
-
A.
Inhulets River
chosen
The Inhulets River is a tributary of the Dnieper in central and southern Ukraine, flowing through industrial cities such as Kryvyi Rih.
-
B.
Vyshny Volochyok
Vyshny Volochyok is a historic town in Tver Oblast, Russia, known as a former key transport hub on the waterway between Moscow and Saint Petersburg.
-
C.
Serebryanye Prudy
Serebryanye Prudy is a rural locality in Moscow Oblast, Russia, historically notable as the birthplace of Soviet Marshal Vasily Chuikov.
-
D.
Urzhum
Urzhum is a small historic town in Kirov Oblast, Russia, known as the birthplace of prominent Soviet leader Sergei Kirov.
-
E.
Yenakiieve
Yenakiieve is an industrial city in eastern Ukraine, historically known for its coal mining and metallurgical industries.
- 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_69a8864b6de0819098d089f6a1b910a7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb14475448190b291ada3454bf98b |
completed | March 7, 2026, 5:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adf3cc8d5c8190bee638183989830c |
completed | March 8, 2026, 10:10 p.m. |
Created at: March 4, 2026, 7:34 p.m.