Triple
T5943352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yevgeny Yevtushenko |
E132219
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object |
Zima
Zima is a small Siberian town in Russia known as the birthplace of poet Yevgeny Yevtushenko.
|
E556597
|
NE FINISHED |
How this triple was built (4 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: Zima | Statement: [Yevgeny Yevtushenko, placeOfBirth, Zima]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zima Context triple: [Yevgeny Yevtushenko, placeOfBirth, Zima]
-
A.
Zima
Zima is a surname most notably associated with a family of American actresses, including Yvonne Zima and her sisters Madeline and Vanessa.
-
B.
Blizne
Blizne is a village in southeastern Poland best known for its historic wooden All Saints Church, a UNESCO World Heritage Site.
-
C.
Śnieżnica
Śnieżnica is a mountain peak in southern Poland, located in the Beskid Wyspowy range and popular for hiking and winter sports.
-
D.
Frunze
Frunze is a surname most notably associated with Mikhail Frunze, a prominent Bolshevik leader and Red Army commander during the Russian Civil War.
-
E.
Prokhladny
Prokhladny is a town in the Kabardino-Balkar Republic of Russia, known as an agricultural and transport center in the North Caucasus region.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Zima Triple: [Yevgeny Yevtushenko, placeOfBirth, Zima]
Generated description
Zima is a small Siberian town in Russia known as the birthplace of poet Yevgeny Yevtushenko.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zima Target entity description: Zima is a small Siberian town in Russia known as the birthplace of poet Yevgeny Yevtushenko.
-
A.
Zima
Zima is a surname most notably associated with a family of American actresses, including Yvonne Zima and her sisters Madeline and Vanessa.
-
B.
Blizne
Blizne is a village in southeastern Poland best known for its historic wooden All Saints Church, a UNESCO World Heritage Site.
-
C.
Śnieżnica
Śnieżnica is a mountain peak in southern Poland, located in the Beskid Wyspowy range and popular for hiking and winter sports.
-
D.
Frunze
Frunze is a surname most notably associated with Mikhail Frunze, a prominent Bolshevik leader and Red Army commander during the Russian Civil War.
-
E.
Prokhladny
Prokhladny is a town in the Kabardino-Balkar Republic of Russia, known as an agricultural and transport center in the North Caucasus region.
- F. None of above. chosen
Provenance (5 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_69c00869d3308190af89b2453e0f7546 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0393641d0819081c6c44816d94e4e |
completed | March 22, 2026, 6:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0c07f9ab081909fe7727837fa7f7a |
completed | March 23, 2026, 4:24 a.m. |
| NEDg | Description generation | batch_69c0c1c02b608190a42850a15cf9d2c6 |
completed | March 23, 2026, 4:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0c443df6c8190b7b566fa46177cfd |
completed | March 23, 2026, 4:40 a.m. |
Created at: March 22, 2026, 4:01 p.m.