Triple

T1985476
Position Surface form Disambiguated ID Type / Status
Subject Tartu E43129 entity
Predicate locatedIn P40 FINISHED
Object Tartu County
Tartu County is an administrative region in eastern Estonia centered around the university city of Tartu and known for its cultural, educational, and economic significance.
E222912 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: Tartu County | Statement: [Tartu, locatedIn, Tartu County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tartu County
Context triple: [Tartu, locatedIn, Tartu County]
  • A. Harku Parish
    Harku Parish is a rural municipality in northern Estonia, located just west of the capital city Tallinn.
  • B. Suuremõisa
    Suuremõisa is a village on the Estonian island of Hiiumaa, known for its historic manor complex and surrounding park.
  • C. Kuressaare
    Kuressaare is the main town on Estonia’s Saaremaa island, known for its well-preserved medieval castle and seaside spa resort atmosphere.
  • D. Viimsi Parish
    Viimsi Parish is a suburban rural municipality in northern Estonia, located on the Viimsi Peninsula just northeast of the capital city Tallinn.
  • E. Kivalliq Region
    Kivalliq Region is an administrative region of Nunavut in northern Canada, known for its Inuit communities, tundra landscapes, and Arctic wildlife.
  • 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: Tartu County
Triple: [Tartu, locatedIn, Tartu County]
Generated description
Tartu County is an administrative region in eastern Estonia centered around the university city of Tartu and known for its cultural, educational, and economic significance.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tartu County
Target entity description: Tartu County is an administrative region in eastern Estonia centered around the university city of Tartu and known for its cultural, educational, and economic significance.
  • A. Harku Parish
    Harku Parish is a rural municipality in northern Estonia, located just west of the capital city Tallinn.
  • B. Suuremõisa
    Suuremõisa is a village on the Estonian island of Hiiumaa, known for its historic manor complex and surrounding park.
  • C. Kuressaare
    Kuressaare is the main town on Estonia’s Saaremaa island, known for its well-preserved medieval castle and seaside spa resort atmosphere.
  • D. Viimsi Parish
    Viimsi Parish is a suburban rural municipality in northern Estonia, located on the Viimsi Peninsula just northeast of the capital city Tallinn.
  • E. Kivalliq Region
    Kivalliq Region is an administrative region of Nunavut in northern Canada, known for its Inuit communities, tundra landscapes, and Arctic wildlife.
  • 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_69a88713ddc88190a969715658ebe7a8 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb821c2d48190abea6c89f37b51b1 completed March 7, 2026, 5:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae0331eec881909463163fb71e4eba completed March 8, 2026, 11:16 p.m.
NEDg Description generation batch_69ae03e575a88190a93181eb9d9bc3eb completed March 8, 2026, 11:19 p.m.
NED2 Entity disambiguation (via description) batch_69ae0473aecc8190b3da07fb8fd18e81 completed March 8, 2026, 11:21 p.m.
Created at: March 4, 2026, 7:37 p.m.