Triple

T21514152
Position Surface form Disambiguated ID Type / Status
Subject Mierzeja Wiślana E530800 entity
Predicate hasSettlement P1068 FINISHED
Object Primorsk
Primorsk is a small coastal town situated on the Vistula Spit, known for its seaside location along the Baltic coast.
E1487867 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: Primorsk | Statement: [Mierzeja Wiślana, hasSettlement, Primorsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Primorsk
Context triple: [Mierzeja Wiślana, hasSettlement, Primorsk]
  • A. Primorsk
    Primorsk is a port town in northwestern Russia situated on the coast of the Gulf of Finland in Leningrad Oblast.
  • B. Primorsko
    Primorsko is a Bulgarian Black Sea coastal town and resort known for its beaches and tourism, located in southeastern Bulgaria.
  • C. Obdorsk
    Obdorsk is the historical name of the Arctic city now known as Salekhard in northwestern Siberia, Russia.
  • D. Imotski
    Imotski is a small historic town in inland Dalmatia, Croatia, known for its karst landscape and the nearby Blue and Red Lakes.
  • E. Svetlogorsk
    Svetlogorsk is an industrial city in southeastern Belarus known for its chemical and pulp-and-paper industries along the Berezina River.
  • 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: Primorsk
Triple: [Mierzeja Wiślana, hasSettlement, Primorsk]
Generated description
Primorsk is a small coastal town situated on the Vistula Spit, known for its seaside location along the Baltic coast.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Primorsk
Target entity description: Primorsk is a small coastal town situated on the Vistula Spit, known for its seaside location along the Baltic coast.
  • A. Primorsk
    Primorsk is a port town in northwestern Russia situated on the coast of the Gulf of Finland in Leningrad Oblast.
  • B. Primorsko
    Primorsko is a Bulgarian Black Sea coastal town and resort known for its beaches and tourism, located in southeastern Bulgaria.
  • C. Obdorsk
    Obdorsk is the historical name of the Arctic city now known as Salekhard in northwestern Siberia, Russia.
  • D. Imotski
    Imotski is a small historic town in inland Dalmatia, Croatia, known for its karst landscape and the nearby Blue and Red Lakes.
  • E. Svetlogorsk
    Svetlogorsk is an industrial city in southeastern Belarus known for its chemical and pulp-and-paper industries along the Berezina River.
  • 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_69e0c45c81f08190a6b8bbb70a45aae7 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9ea88e6fc8190a4b73b8d32dae5a8 completed April 23, 2026, 9:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a09e145ac5c8190a05cc2a80d28cac3 completed May 17, 2026, 3:39 p.m.
NEDg Description generation batch_6a09e1fc4f7881909e198768cdb43747 completed May 17, 2026, 3:42 p.m.
NED2 Entity disambiguation (via description) batch_6a09e2c86858819092216c12d8aa3348 completed May 17, 2026, 3:46 p.m.
Created at: April 16, 2026, 6:25 p.m.