Triple
T8833532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prof. Dr. Asen Zlatarov University |
E210204
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
Asen Zlatarov
Asen Zlatarov was a prominent Bulgarian chemist, writer, and public figure known for his contributions to science, literature, and education in Bulgaria.
|
E760026
|
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: Asen Zlatarov | Statement: [Prof. Dr. Asen Zlatarov University, namedAfter, Asen Zlatarov]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Asen Zlatarov Context triple: [Prof. Dr. Asen Zlatarov University, namedAfter, Asen Zlatarov]
-
A.
Alexander Toshev
Alexander Toshev is a computer scientist known for his contributions to computer vision and deep learning, including influential work on object detection.
-
B.
Georgi Todorov
Georgi Todorov was a Bulgarian general who played a prominent command role in the Balkan Wars and World War I.
-
C.
Vasil Terziev
Vasil Terziev is a Bulgarian entrepreneur and politician who serves as the mayor of Sofia.
-
D.
Todor Popov
Todor Popov is a Bulgarian politician who serves as the long-time mayor of the city of Pazardzhik.
-
E.
Najden Gerov
Najden Gerov was a prominent 19th-century Bulgarian educator, linguist, and public figure known for his major contributions to Bulgarian language studies and national cultural awakening.
- 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: Asen Zlatarov Triple: [Prof. Dr. Asen Zlatarov University, namedAfter, Asen Zlatarov]
Generated description
Asen Zlatarov was a prominent Bulgarian chemist, writer, and public figure known for his contributions to science, literature, and education in Bulgaria.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Asen Zlatarov Target entity description: Asen Zlatarov was a prominent Bulgarian chemist, writer, and public figure known for his contributions to science, literature, and education in Bulgaria.
-
A.
Alexander Toshev
Alexander Toshev is a computer scientist known for his contributions to computer vision and deep learning, including influential work on object detection.
-
B.
Georgi Todorov
Georgi Todorov was a Bulgarian general who played a prominent command role in the Balkan Wars and World War I.
-
C.
Vasil Terziev
Vasil Terziev is a Bulgarian entrepreneur and politician who serves as the mayor of Sofia.
-
D.
Todor Popov
Todor Popov is a Bulgarian politician who serves as the long-time mayor of the city of Pazardzhik.
-
E.
Najden Gerov
Najden Gerov was a prominent 19th-century Bulgarian educator, linguist, and public figure known for his major contributions to Bulgarian language studies and national cultural awakening.
- 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_69ca8388549c819095fd94eadefbb007 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc60670fa48190b2a873f6498de7f6 |
completed | April 1, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf8975a6f481908ee435d0435c8ffb |
completed | April 3, 2026, 9:33 a.m. |
| NEDg | Description generation | batch_69cf8a8e5db0819080e6fdc3d8322e94 |
completed | April 3, 2026, 9:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cf8b8849ec8190915fa087b1b46c18 |
completed | April 3, 2026, 9:42 a.m. |
Created at: March 30, 2026, 6:47 p.m.