Triple
T10706870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elem Klimov |
E252430
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object |
Anton Klimov
Anton Klimov is known primarily as the son of renowned Soviet film director Elem Klimov.
|
E1046211
|
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: Anton Klimov | Statement: [Elem Klimov, child, Anton Klimov]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anton Klimov Context triple: [Elem Klimov, child, Anton Klimov]
-
A.
Alexey Shchusev
Alexey Shchusev was a prominent Russian and Soviet architect known for blending traditional Russian styles with modernist principles in major state and religious buildings.
-
B.
Oleg Klimov
Oleg Klimov is a researcher known for his contributions to the development and analysis of Proximal Policy Optimization (PPO) algorithms in reinforcement learning.
-
C.
Viktor Kudriavtsev
Viktor Kudriavtsev is a renowned Russian figure skating coach known for developing numerous elite skaters, including Olympic champion Ilia Kulik.
-
D.
Makar Devushkin
Makar Devushkin is the humble, impoverished copy clerk and epistolary narrator at the heart of Fyodor Dostoevsky’s novel "Poor Folk," whose letters reveal his inner life and social misery.
-
E.
Mikhail Posokhin
Mikhail Posokhin was a prominent Soviet architect known for major state projects in Moscow, including landmark government and cultural buildings.
- 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: Anton Klimov Triple: [Elem Klimov, child, Anton Klimov]
Generated description
Anton Klimov is known primarily as the son of renowned Soviet film director Elem Klimov.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Anton Klimov Target entity description: Anton Klimov is known primarily as the son of renowned Soviet film director Elem Klimov.
-
A.
Alexey Shchusev
Alexey Shchusev was a prominent Russian and Soviet architect known for blending traditional Russian styles with modernist principles in major state and religious buildings.
-
B.
Oleg Klimov
Oleg Klimov is a researcher known for his contributions to the development and analysis of Proximal Policy Optimization (PPO) algorithms in reinforcement learning.
-
C.
Viktor Kudriavtsev
Viktor Kudriavtsev is a renowned Russian figure skating coach known for developing numerous elite skaters, including Olympic champion Ilia Kulik.
-
D.
Makar Devushkin
Makar Devushkin is the humble, impoverished copy clerk and epistolary narrator at the heart of Fyodor Dostoevsky’s novel "Poor Folk," whose letters reveal his inner life and social misery.
-
E.
Mikhail Posokhin
Mikhail Posokhin was a prominent Soviet architect known for major state projects in Moscow, including landmark government and cultural buildings.
- 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_69d6aa5cbabc8190973e683950d89faf |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fddfbed48190810bb3faee473fde |
completed | April 9, 2026, 1:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75d756bd08190a79adc9a2e6188ed |
completed | May 3, 2026, 2:36 p.m. |
| NEDg | Description generation | batch_69f75e30545c8190b47bd1e06411a163 |
completed | May 3, 2026, 2:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f75e9fc1508190800291a16840a9a8 |
completed | May 3, 2026, 2:41 p.m. |
Created at: April 8, 2026, 9:12 p.m.