Triple
T11098763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teichmüller curve |
E262445
|
entity |
| Predicate | studiedBy |
P1945
|
FINISHED |
| Object |
Anton Zorich
Anton Zorich is a mathematician known for his contributions to dynamical systems, flat surfaces, and Teichmüller theory.
|
E918496
|
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 Zorich | Statement: [Teichmüller curve, studiedBy, Anton Zorich]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anton Zorich Context triple: [Teichmüller curve, studiedBy, Anton Zorich]
-
A.
Yuri Nikulin
Yuri Nikulin was a beloved Soviet and Russian clown and film actor, renowned for his work in the Moscow Circus on Tsvetnoy Boulevard and for starring in many classic Soviet comedies.
-
B.
Vladimir Gelfreikh
Vladimir Gelfreikh was a Soviet architect known for his prominent Stalinist-era designs and contributions to major state buildings in Moscow.
-
C.
Mikhail Brin
Mikhail Brin is a Soviet-born mathematician and academic, best known as the father of Google co-founder Sergey Brin.
-
D.
Vladimir Bogomolov
Vladimir Bogomolov was a Soviet writer best known for his war-themed fiction, some of which was adapted into notable films.
-
E.
Grigory Yevdokimov
Grigory Yevdokimov was a Soviet political figure and Old Bolshevik who became one of the accused in Stalin’s Great Purge show trials.
- 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 Zorich Triple: [Teichmüller curve, studiedBy, Anton Zorich]
Generated description
Anton Zorich is a mathematician known for his contributions to dynamical systems, flat surfaces, and Teichmüller theory.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Anton Zorich Target entity description: Anton Zorich is a mathematician known for his contributions to dynamical systems, flat surfaces, and Teichmüller theory.
-
A.
Yuri Nikulin
Yuri Nikulin was a beloved Soviet and Russian clown and film actor, renowned for his work in the Moscow Circus on Tsvetnoy Boulevard and for starring in many classic Soviet comedies.
-
B.
Vladimir Gelfreikh
Vladimir Gelfreikh was a Soviet architect known for his prominent Stalinist-era designs and contributions to major state buildings in Moscow.
-
C.
Mikhail Brin
Mikhail Brin is a Soviet-born mathematician and academic, best known as the father of Google co-founder Sergey Brin.
-
D.
Vladimir Bogomolov
Vladimir Bogomolov was a Soviet writer best known for his war-themed fiction, some of which was adapted into notable films.
-
E.
Grigory Yevdokimov
Grigory Yevdokimov was a Soviet political figure and Old Bolshevik who became one of the accused in Stalin’s Great Purge show trials.
- 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_69d6aa9a40d88190a373e2c7e48285db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79a0c46308190889b94c23ebaca62 |
completed | April 9, 2026, 12:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5254907348190a9652395f15b2044 |
completed | April 19, 2026, 6:56 p.m. |
| NEDg | Description generation | batch_69e52c81449c8190847b64fa91a45b2e |
completed | April 19, 2026, 7:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e5319b6ef0819096debabfb6ffbe70 |
completed | April 19, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:27 p.m.