Triple
T6843540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Klyazma River |
E157834
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Orekhovo-Zuyevo |
E128774
|
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: Orekhovo-Zuyevo | Statement: [Klyazma River, flowsThrough, Orekhovo-Zuyevo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orekhovo-Zuyevo Context triple: [Klyazma River, flowsThrough, Orekhovo-Zuyevo]
-
A.
Serpukhov
Serpukhov is a historic Russian town south of Moscow known for its medieval monasteries, industrial heritage, and location on the Nara River.
-
B.
Lyubertsy
Lyubertsy is a city in Russia that serves as a major suburban and industrial center just southeast of Moscow.
-
C.
Noginsk
chosen
Noginsk is a town in western Russia that serves as an industrial and transport center east of Moscow.
-
D.
Orekhovo
Orekhovo is a Moscow Metro station on the Zamoskvoretskaya Line serving the Orekhovo-Borisovo district in southern Moscow.
-
E.
Zelenogradsk
Zelenogradsk is a coastal resort town in Russia’s Kaliningrad Oblast on the Baltic Sea, known for its beaches, historic architecture, and proximity to the Curonian Spit.
- 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_69c6882ed4c081909dc465a7cf8838be |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d6b7179481909e3482fef47b2719 |
completed | March 27, 2026, 7:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8109adff8819081426b44ae70bdfb |
completed | March 28, 2026, 5:32 p.m. |
Created at: March 27, 2026, 2:19 p.m.