Triple
T18464882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stalino |
E451133
|
entity |
| Predicate | hasNameInLanguage |
P15
|
FINISHED |
| Object | Сталино |
—
|
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: Сталино | Statement: [Stalino, hasNameInLanguage, Сталино]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Сталино Context triple: [Stalino, hasNameInLanguage, Сталино]
-
A.
Stalino
chosen
Stalino was the Soviet-era name of the industrial city now known as Donetsk in eastern Ukraine.
-
B.
Klimowitschi
Klimowitschi is a town in Belarus known in part for its international municipal partnership with Werder (Havel) in Germany.
-
C.
Stalinets
Stalinets was the former name of the Russian football club now known as Lokomotiv Moscow.
-
D.
Kuibyshev
Kuibyshev is the former Soviet name of the Russian city now known as Samara, a major industrial and administrative center on the Volga River.
-
E.
Tolbukhin
Tolbukhin is a Russian surname most notably associated with Soviet military commander Fyodor Tolbukhin, a prominent general during World War II.
- 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_69d8d38345688190b565eac2e4cd7935 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e52a82920081909b2b89125db5982a |
completed | April 19, 2026, 7:18 p.m. |
Created at: April 10, 2026, 11:33 a.m.