Triple

T10343591
Position Surface form Disambiguated ID Type / Status
Subject Peretz Smolenskin E243685 entity
Predicate familyName P18 FINISHED
Object Smolenskin
Smolenskin is the surname of Peretz Smolenskin, a prominent 19th-century Hebrew novelist and key figure in the Jewish Enlightenment (Haskalah) movement.
E866045 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: Smolenskin | Statement: [Peretz Smolenskin, familyName, Smolenskin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Smolenskin
Context triple: [Peretz Smolenskin, familyName, Smolenskin]
  • A. Kozelsk
    Kozelsk is a historic town in western Russia known for its medieval defenses and location within Kaluga Oblast.
  • B. Kurskaya
    Kurskaya is a Moscow Metro station on the Koltsevaya (Circle) Line, serving as a major transfer hub in the city’s rapid transit network.
  • C. Maloyaroslavets
    Maloyaroslavets is a historic town in western Russia known for the 1812 Battle of Maloyaroslavets during Napoleon’s invasion.
  • D. Smolensk
    Smolensk is a historic city in western Russia near the Belarusian border, known for its strategic location and centuries-old fortifications.
  • E. Krasnov
    Krasnov is a Russian surname borne by various notable figures in military, political, and cultural history.
  • 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: Smolenskin
Triple: [Peretz Smolenskin, familyName, Smolenskin]
Generated description
Smolenskin is the surname of Peretz Smolenskin, a prominent 19th-century Hebrew novelist and key figure in the Jewish Enlightenment (Haskalah) movement.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Smolenskin
Target entity description: Smolenskin is the surname of Peretz Smolenskin, a prominent 19th-century Hebrew novelist and key figure in the Jewish Enlightenment (Haskalah) movement.
  • A. Kozelsk
    Kozelsk is a historic town in western Russia known for its medieval defenses and location within Kaluga Oblast.
  • B. Kurskaya
    Kurskaya is a Moscow Metro station on the Koltsevaya (Circle) Line, serving as a major transfer hub in the city’s rapid transit network.
  • C. Maloyaroslavets
    Maloyaroslavets is a historic town in western Russia known for the 1812 Battle of Maloyaroslavets during Napoleon’s invasion.
  • D. Smolensk
    Smolensk is a historic city in western Russia near the Belarusian border, known for its strategic location and centuries-old fortifications.
  • E. Krasnov
    Krasnov is a Russian surname borne by various notable figures in military, political, and cultural history.
  • 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_69d381b22b8c8190aaed476be5f872a9 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e92105888190a08104deb9d0cf1c completed April 7, 2026, 11:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69d89f45e8c0819091f9397619354882 completed April 10, 2026, 6:57 a.m.
NEDg Description generation batch_69d8a43ae8a48190b1c05b6a91dfed9a completed April 10, 2026, 7:18 a.m.
NED2 Entity disambiguation (via description) batch_69d8b8fe1b9c8190b5a4787797ad7120 completed April 10, 2026, 8:46 a.m.
Created at: April 6, 2026, 11:55 a.m.