Triple
T413921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karl Marx Monument |
E9549
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object |
Lev Kerbel
Lev Kerbel was a prominent Soviet sculptor renowned for his monumental public works and statues of communist leaders.
|
E68511
|
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: Lev Kerbel | Statement: [Karl Marx Monument, creator, Lev Kerbel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lev Kerbel Context triple: [Karl Marx Monument, creator, Lev Kerbel]
-
A.
Nicholas Sagan
Nicholas Sagan is the son of science communicator Ann Druyan and famed astronomer Carl Sagan.
-
B.
John David Stier
John David Stier is the son of Nobel Prize–winning mathematician John Nash and Eleanor Stier.
-
C.
Sergei Brylin
Sergei Brylin is a former Russian professional ice hockey forward best known for his long NHL career with the New Jersey Devils, with whom he won three Stanley Cup championships.
-
D.
Philip M. Kaiser
Philip M. Kaiser was an American diplomat and public servant who held several key ambassadorial posts during the Cold War era.
-
E.
Stanley Corrsin
Stanley Corrsin was a prominent American fluid dynamicist renowned for his pioneering contributions to the study of turbulence and mixing in fluid flows.
- 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: Lev Kerbel Triple: [Karl Marx Monument, creator, Lev Kerbel]
Generated description
Lev Kerbel was a prominent Soviet sculptor renowned for his monumental public works and statues of communist leaders.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lev Kerbel Target entity description: Lev Kerbel was a prominent Soviet sculptor renowned for his monumental public works and statues of communist leaders.
-
A.
Nicholas Sagan
Nicholas Sagan is the son of science communicator Ann Druyan and famed astronomer Carl Sagan.
-
B.
John David Stier
John David Stier is the son of Nobel Prize–winning mathematician John Nash and Eleanor Stier.
-
C.
Sergei Brylin
Sergei Brylin is a former Russian professional ice hockey forward best known for his long NHL career with the New Jersey Devils, with whom he won three Stanley Cup championships.
-
D.
Philip M. Kaiser
Philip M. Kaiser was an American diplomat and public servant who held several key ambassadorial posts during the Cold War era.
-
E.
Stanley Corrsin
Stanley Corrsin was a prominent American fluid dynamicist renowned for his pioneering contributions to the study of turbulence and mixing in fluid flows.
- 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_69a2e80111fc8190961d5b7c6154123f |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ecdd3d1c8190a31b071569cfc980 |
completed | Feb. 28, 2026, 1:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4d03b948c8190b9b6f8e86c3249e8 |
completed | March 1, 2026, 11:48 p.m. |
| NEDg | Description generation | batch_69a4d106a1248190a06b340210767bc9 |
completed | March 1, 2026, 11:51 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a4de9182dc8190b62c2ea6d032e9bc |
completed | March 2, 2026, 12:49 a.m. |
Created at: Feb. 28, 2026, 1:09 p.m.