Triple

T5051659
Position Surface form Disambiguated ID Type / Status
Subject Harju County E113798 entity
Predicate contains P35 FINISHED
Object Maardu
Maardu is an industrial town in northern Estonia, located just east of the capital Tallinn in Harju County.
 E491064 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: Maardu | Statement: [Harju County, contains, Maardu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Maardu
Context triple: [Harju County, contains, Maardu]
  • A. Pärnu
    Pärnu is a coastal city in southwestern Estonia known as a popular summer resort and spa destination on the Baltic Sea.
  • B. Tallinn
    Tallinn is the capital and largest city of Estonia, a historic Baltic Sea port known for its well-preserved medieval Old Town and strategic maritime location.
  • C. Tartu
    Tartu is Estonia’s second-largest city and a historic cultural and intellectual center, best known as the country’s main university town.
  • D. Kuressaare
    Kuressaare is the main town on Estonia’s Saaremaa island, known for its well-preserved medieval castle and seaside spa resort atmosphere.
  • E. Narva
    Narva is a historic city in northeastern Estonia on the border with Russia, known for its strategic military importance and well-preserved fortress overlooking the Narva 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: Maardu
Triple: [Harju County, contains, Maardu]
Generated description
Maardu is an industrial town in northern Estonia, located just east of the capital Tallinn in Harju County.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Maardu
Target entity description: Maardu is an industrial town in northern Estonia, located just east of the capital Tallinn in Harju County.
  • A. Pärnu
    Pärnu is a coastal city in southwestern Estonia known as a popular summer resort and spa destination on the Baltic Sea.
  • B. Tallinn
    Tallinn is the capital and largest city of Estonia, a historic Baltic Sea port known for its well-preserved medieval Old Town and strategic maritime location.
  • C. Tartu
    Tartu is Estonia’s second-largest city and a historic cultural and intellectual center, best known as the country’s main university town.
  • D. Kuressaare
    Kuressaare is the main town on Estonia’s Saaremaa island, known for its well-preserved medieval castle and seaside spa resort atmosphere.
  • E. Narva
    Narva is a historic city in northeastern Estonia on the border with Russia, known for its strategic military importance and well-preserved fortress overlooking the Narva 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_69bd443aa1f88190abb992d138f2cf42 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7426fc8081908a8227f73168c235 completed March 20, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69bea483b6cc8190b3b48598a291d708 completed March 21, 2026, 2 p.m.
NEDg Description generation batch_69bea5e902a88190a96a0dea88d3952e completed March 21, 2026, 2:06 p.m.
NED2 Entity disambiguation (via description) batch_69bea9961f8c8190b7ac93e199aa76d7 completed March 21, 2026, 2:22 p.m.
Created at: March 20, 2026, 1:37 p.m.