Triple
T23511948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zvenigorod |
E572448
|
entity |
| Predicate | historicalRegion |
P915
|
FINISHED |
| Object | Zalesye |
—
|
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: Zalesye | Statement: [Zvenigorod, historicalRegion, Zalesye]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zalesye Context triple: [Zvenigorod, historicalRegion, Zalesye]
-
A.
Zalesye
chosen
Zalesye is a historic region in northeastern European Russia that served as an early center of medieval Rus’ settlement and state formation.
-
B.
Zolotonosha
Zolotonosha is a historic town in central Ukraine, located in the Cherkasy region on the banks of the Zolotonoshka River.
-
C.
Zaosie
Zaosie is a small village in present-day Belarus, best known as the birthplace of the Polish Romantic poet Adam Mickiewicz.
-
D.
Zalesie
Zalesie is a historic, villa-filled residential neighborhood in the Śródmieście district of Wrocław, known for its green spaces and proximity to the Oder River.
-
E.
Orlovets
Orlovets is a prominent mountain peak in Bulgaria’s Rila Mountains, popular with hikers and climbers for its rugged alpine terrain and scenic views.
- 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_69e245b5e4208190bac8a6509867e394 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1aa7f583881909e78e8fe2e6e25fe |
completed | April 29, 2026, 6:51 a.m. |
Created at: April 17, 2026, 6:07 p.m.