Triple
T950383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vyacheslav Molotov |
E20506
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object |
Kukarka
Kukarka is a small Russian locality historically known as the birthplace of Soviet politician Vyacheslav Molotov.
|
E117121
|
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: Kukarka | Statement: [Vyacheslav Molotov, placeOfBirth, Kukarka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kukarka Context triple: [Vyacheslav Molotov, placeOfBirth, Kukarka]
-
A.
Alupka
Alupka is a resort town on the southern coast of Crimea, known for the Neo-Gothic and Moorish-style Vorontsov Palace and its scenic location at the foot of Mount Ai-Petri.
-
B.
Sivaraksa
Sivaraksa is the surname of Sulak Sivaraksa, a prominent Thai social activist, intellectual, and proponent of engaged Buddhism.
-
C.
Pucikwar
Pucikwar is an extinct Great Andamanese language once spoken by the Pucikwar people of the Andaman Islands in India.
-
D.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
-
E.
Krakhuna
Krakhuna is a Georgian white grape variety from the Imereti region, known for producing aromatic, full-bodied wines with pronounced acidity.
- 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: Kukarka Triple: [Vyacheslav Molotov, placeOfBirth, Kukarka]
Generated description
Kukarka is a small Russian locality historically known as the birthplace of Soviet politician Vyacheslav Molotov.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kukarka Target entity description: Kukarka is a small Russian locality historically known as the birthplace of Soviet politician Vyacheslav Molotov.
-
A.
Alupka
Alupka is a resort town on the southern coast of Crimea, known for the Neo-Gothic and Moorish-style Vorontsov Palace and its scenic location at the foot of Mount Ai-Petri.
-
B.
Sivaraksa
Sivaraksa is the surname of Sulak Sivaraksa, a prominent Thai social activist, intellectual, and proponent of engaged Buddhism.
-
C.
Pucikwar
Pucikwar is an extinct Great Andamanese language once spoken by the Pucikwar people of the Andaman Islands in India.
-
D.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
-
E.
Krakhuna
Krakhuna is a Georgian white grape variety from the Imereti region, known for producing aromatic, full-bodied wines with pronounced acidity.
- 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_69a493b0f2fc81908cd227480a5356a1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3d62e408190855b2883407f6c6b |
completed | March 1, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac25845f588190b0f60754636a88d0 |
completed | March 7, 2026, 1:17 p.m. |
| NEDg | Description generation | batch_69ac2674f5b88190bb3416a249a63982 |
completed | March 7, 2026, 1:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac2704de788190857a3104180ccd21 |
completed | March 7, 2026, 1:24 p.m. |
Created at: March 1, 2026, 7:40 p.m.