Triple
T14307534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chersky Range |
E354735
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
Jan Czerski
Jan Czerski was a Polish-Russian geologist and explorer renowned for his pioneering research on Siberia’s geology and paleontology in the 19th century.
|
E1152692
|
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: Jan Czerski | Statement: [Chersky Range, namedAfter, Jan Czerski]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jan Czerski Context triple: [Chersky Range, namedAfter, Jan Czerski]
-
A.
Jan Szczepanik
Jan Szczepanik was a Polish inventor known as the "Polish Edison" for his numerous innovations in photography, weaving, and early color film technology.
-
B.
Jan Kiepura
Jan Kiepura was a renowned Polish tenor and film actor of the early 20th century, celebrated for his powerful voice and international opera and cinema career.
-
C.
Jan Zaleski
Jan Zaleski was a Polish biochemist known for his pioneering research in organic and physiological chemistry in the early 20th century.
-
D.
Cezary Skubiszewski
Cezary Skubiszewski is a Polish-born Australian composer known for his acclaimed film and television scores.
-
E.
Andrzej Chyra
Andrzej Chyra is a Polish film and theater actor known for his versatile performances in contemporary Polish cinema.
- 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: Jan Czerski Triple: [Chersky Range, namedAfter, Jan Czerski]
Generated description
Jan Czerski was a Polish-Russian geologist and explorer renowned for his pioneering research on Siberia’s geology and paleontology in the 19th century.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jan Czerski Target entity description: Jan Czerski was a Polish-Russian geologist and explorer renowned for his pioneering research on Siberia’s geology and paleontology in the 19th century.
-
A.
Jan Szczepanik
Jan Szczepanik was a Polish inventor known as the "Polish Edison" for his numerous innovations in photography, weaving, and early color film technology.
-
B.
Jan Kiepura
Jan Kiepura was a renowned Polish tenor and film actor of the early 20th century, celebrated for his powerful voice and international opera and cinema career.
-
C.
Jan Zaleski
Jan Zaleski was a Polish biochemist known for his pioneering research in organic and physiological chemistry in the early 20th century.
-
D.
Cezary Skubiszewski
Cezary Skubiszewski is a Polish-born Australian composer known for his acclaimed film and television scores.
-
E.
Andrzej Chyra
Andrzej Chyra is a Polish film and theater actor known for his versatile performances in contemporary Polish cinema.
- 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_69d8278ed42c8190b9f882dcce611347 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de85b156b0819083f2bd319deed1b6 |
completed | April 14, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff0b3017808190a44087056ba6a472 |
completed | May 9, 2026, 10:23 a.m. |
| NEDg | Description generation | batch_69ff0bb903f881909619cece7def68e4 |
completed | May 9, 2026, 10:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff0c81636c81909536e69b48c5c400 |
completed | May 9, 2026, 10:29 a.m. |
Created at: April 10, 2026, 1:12 a.m.