Triple

T9313563
Position Surface form Disambiguated ID Type / Status
Subject Minsk Region E224062 entity
Predicate contains P35 FINISHED
Object Logoisk
Logoisk is a small historic town in Belarus known for its scenic hilly landscape, ski resort, and archaeological heritage.
 E791355 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: Logoisk | Statement: [Minsk Region, contains, Logoisk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Logoisk
Context triple: [Minsk Region, contains, Logoisk]
  • A. The Logo
    The Logo is the famous nickname of NBA legend Jerry West, referencing his iconic silhouette used in the league’s official logo.
  • B. Logos
    Logos is a central concept in Christian theology referring to the divine Word or reason of God, identified with Christ as the preexistent and incarnate Son.
  • C. Loggos
    Loggos is a small, picturesque coastal village on the Greek island of Paxos, known for its harbor, traditional tavernas, and relaxed atmosphere.
  • D. Logo
    Logo is an educational programming language known for its turtle graphics, designed to help learners explore mathematical and computational ideas through simple commands.
  • E. Iconi
    Iconi is a historic coastal town on Grande Comore in the Comoros, known for its traditional architecture and role in the island’s early political and cultural life.
  • 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: Logoisk
Triple: [Minsk Region, contains, Logoisk]
Generated description
Logoisk is a small historic town in Belarus known for its scenic hilly landscape, ski resort, and archaeological heritage.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Logoisk
Target entity description: Logoisk is a small historic town in Belarus known for its scenic hilly landscape, ski resort, and archaeological heritage.
  • A. The Logo
    The Logo is the famous nickname of NBA legend Jerry West, referencing his iconic silhouette used in the league’s official logo.
  • B. Logos
    Logos is a central concept in Christian theology referring to the divine Word or reason of God, identified with Christ as the preexistent and incarnate Son.
  • C. Loggos
    Loggos is a small, picturesque coastal village on the Greek island of Paxos, known for its harbor, traditional tavernas, and relaxed atmosphere.
  • D. Logo
    Logo is an educational programming language known for its turtle graphics, designed to help learners explore mathematical and computational ideas through simple commands.
  • E. Iconi
    Iconi is a historic coastal town on Grande Comore in the Comoros, known for its traditional architecture and role in the island’s early political and cultural life.
  • 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_69ca8425f4fc81909c1c586e9a5b7530 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd20b048a081909fd7ec0b6b863063 completed April 1, 2026, 1:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0c7a0adc4819097ac906f03f0188e completed April 4, 2026, 8:11 a.m.
NEDg Description generation batch_69d0c8a7190c819097e71c15f7924268 completed April 4, 2026, 8:15 a.m.
NED2 Entity disambiguation (via description) batch_69d0c9e7e7d08190bddc6786f0fcea9e completed April 4, 2026, 8:20 a.m.
Created at: March 30, 2026, 7:37 p.m.