Triple
T16182446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Veselin Topalov |
E392717
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Veselin
Veselin is a masculine given name commonly used in Slavic countries, particularly Bulgaria and other parts of Eastern Europe.
|
E1199297
|
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: Veselin | Statement: [Veselin Topalov, givenName, Veselin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Veselin Context triple: [Veselin Topalov, givenName, Veselin]
-
A.
Vlatko
Vlatko is a masculine given name commonly used in Slavic countries, particularly in North Macedonia and other parts of the Balkans.
-
B.
Dimitar
Dimitar is a masculine given name of Slavic origin, commonly used in Bulgaria and other Eastern European countries.
-
C.
Vaslav
Vaslav is the given name of Vaslav Nijinsky, the legendary early 20th-century ballet dancer and choreographer renowned for his groundbreaking work with the Ballets Russes.
-
D.
Lyudvig Chibirov
Lyudvig Chibirov is an Ossetian politician who became the inaugural leader of the self-proclaimed Republic of South Ossetia following the dissolution of the Soviet Union.
-
E.
Veselin Stoyanov
Veselin Stoyanov is a computer scientist and researcher known for his work in natural language processing and machine learning.
- 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: Veselin Triple: [Veselin Topalov, givenName, Veselin]
Generated description
Veselin is a masculine given name commonly used in Slavic countries, particularly Bulgaria and other parts of Eastern Europe.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Veselin Target entity description: Veselin is a masculine given name commonly used in Slavic countries, particularly Bulgaria and other parts of Eastern Europe.
-
A.
Vlatko
Vlatko is a masculine given name commonly used in Slavic countries, particularly in North Macedonia and other parts of the Balkans.
-
B.
Dimitar
Dimitar is a masculine given name of Slavic origin, commonly used in Bulgaria and other Eastern European countries.
-
C.
Vaslav
Vaslav is the given name of Vaslav Nijinsky, the legendary early 20th-century ballet dancer and choreographer renowned for his groundbreaking work with the Ballets Russes.
-
D.
Lyudvig Chibirov
Lyudvig Chibirov is an Ossetian politician who became the inaugural leader of the self-proclaimed Republic of South Ossetia following the dissolution of the Soviet Union.
-
E.
Veselin Stoyanov
Veselin Stoyanov is a computer scientist and researcher known for his work in natural language processing and machine learning.
- 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2205ef39081908da383abdebc2ccc |
completed | April 17, 2026, 11:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffff03400481908e66db8cf0213c15 |
completed | May 10, 2026, 3:44 a.m. |
| NEDg | Description generation | batch_6a0000ceba648190ac5ecefd34f10d4e |
completed | May 10, 2026, 3:51 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00013fdb1c8190add653fc1cf30e44 |
completed | May 10, 2026, 3:53 a.m. |
Created at: April 10, 2026, 5:02 a.m.