Triple
T14038001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Icebreaker Krasin |
E337762
|
entity |
| Predicate | renamed |
P1742
|
FINISHED |
| Object |
Krasin
Krasin is a historic Russian icebreaker, originally launched in the early 20th century, renowned for Arctic exploration and rescue missions.
|
E1075092
|
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: Krasin | Statement: [Icebreaker Krasin, renamed, Krasin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Krasin Context triple: [Icebreaker Krasin, renamed, Krasin]
-
A.
Jurjev
Jurjev is a historical name for the Estonian city of Tartu, reflecting its past under various regional powers.
-
B.
Czarna Górna
Czarna Górna is a village in southeastern Poland located within the administrative district of Gmina Rymanów in the Subcarpathian region.
-
C.
Belic
Belic is a small settlement located near Playa Las Coloradas on the coast of Cuba.
-
D.
Dragaš
Dragaš is a Serbian medieval noble family name most notably borne by Helena Dragaš, the Byzantine empress and mother of the last Byzantine emperor, Constantine XI Palaiologos.
-
E.
Preobrajenska
Preobrajenska is a Russian surname most notably associated with Olga Preobrajenska, a celebrated ballerina and influential ballet teacher of the late 19th and early 20th centuries.
- 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: Krasin Triple: [Icebreaker Krasin, renamed, Krasin]
Generated description
Krasin is a historic Russian icebreaker, originally launched in the early 20th century, renowned for Arctic exploration and rescue missions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Krasin Target entity description: Krasin is a historic Russian icebreaker, originally launched in the early 20th century, renowned for Arctic exploration and rescue missions.
-
A.
Jurjev
Jurjev is a historical name for the Estonian city of Tartu, reflecting its past under various regional powers.
-
B.
Czarna Górna
Czarna Górna is a village in southeastern Poland located within the administrative district of Gmina Rymanów in the Subcarpathian region.
-
C.
Belic
Belic is a small settlement located near Playa Las Coloradas on the coast of Cuba.
-
D.
Dragaš
Dragaš is a Serbian medieval noble family name most notably borne by Helena Dragaš, the Byzantine empress and mother of the last Byzantine emperor, Constantine XI Palaiologos.
-
E.
Preobrajenska
Preobrajenska is a Russian surname most notably associated with Olga Preobrajenska, a celebrated ballerina and influential ballet teacher of the late 19th and early 20th centuries.
- 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_69d81c664e48819088cbd8f433aeffe5 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de30ee374081908b6b5e8f81dd90f2 |
completed | April 14, 2026, 12:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbc33bc20081909abea7e64d1bd578 |
completed | May 6, 2026, 10:39 p.m. |
| NEDg | Description generation | batch_69fbc53729d081908b74532d2ed54b7a |
completed | May 6, 2026, 10:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fbc5d76cdc8190970778580437cf72 |
completed | May 6, 2026, 10:51 p.m. |
Created at: April 9, 2026, 10:20 p.m.