Triple
T17659124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bila Tserkva Raion |
E440203
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Tarashcha |
—
|
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: Tarashcha | Statement: [Bila Tserkva Raion, containsSettlement, Tarashcha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tarashcha Context triple: [Bila Tserkva Raion, containsSettlement, Tarashcha]
-
A.
Tarashcha
chosen
Tarashcha is a small historic town in central Ukraine, known as the birthplace of prominent Yiddish theater actor and producer Boris Thomashefsky.
-
B.
Zhukhrai
Zhukhrai is a supporting character in Nikolai Ostrovsky’s socialist realist novel "How the Steel Was Tempered," serving as a revolutionary mentor figure who helps shape the protagonist’s political consciousness.
-
C.
Terebovlia
Terebovlia is a historic town in western Ukraine known for its medieval fortress ruins and role as a regional cultural center.
-
D.
Terekhovo
Terekhovo is a metro station on Moscow’s Big Circle Line, serving the Terekhovo area in the western part of the city.
-
E.
Zolotonosha
Zolotonosha is a historic town in central Ukraine, located in the Cherkasy region on the banks of the Zolotonoshka River.
- 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_69d8b9e87e18819087104a44dc4dc5b1 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46ea469448190b2753571f8493aef |
completed | April 19, 2026, 5:56 a.m. |
Created at: April 10, 2026, 9:39 a.m.