Triple

T22783608
Position Surface form Disambiguated ID Type / Status
Subject Hartford metropolitan area E563903 entity
Predicate principalCity P3940 FINISHED
Object Berlin
Berlin is a town in central Connecticut, United States, known as a suburban community within the Greater Hartford region.
E1555246 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: Berlin | Statement: [Hartford metropolitan area, principalCity, Berlin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berlin
Context triple: [Hartford metropolitan area, principalCity, Berlin]
  • A. Berlin
    Berlin is a themed area in the Phantasialand amusement park that recreates the atmosphere and architecture of early 20th-century Berlin.
  • B. Berlin
    Berlin is the capital and largest city of Germany, historically significant as a focal point of Cold War tensions and a major cultural, political, and economic center in Europe.
  • C. Berlin
    Berlin is a charismatic, calculating, and morally ambiguous mastermind and heist leader in the Spanish television series "Money Heist" (La Casa de Papel).
  • D. Berlin
    Berlin is a small town in South Africa’s Eastern Cape province, situated within the Buffalo City Metropolitan Municipality near East London.
  • E. Berlin
    Berlin is a major Ethereum network upgrade that introduced various gas cost optimizations and transaction processing improvements to enhance the blockchain’s efficiency and performance.
  • 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: Berlin
Triple: [Hartford metropolitan area, principalCity, Berlin]
Generated description
Berlin is a town in central Connecticut, United States, known as a suburban community within the Greater Hartford region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Berlin
Target entity description: Berlin is a town in central Connecticut, United States, known as a suburban community within the Greater Hartford region.
  • A. Berlin
    Berlin is a borough in Camden County, New Jersey, known as a suburban community within the Philadelphia metropolitan area.
  • B. Berlin
    Berlin is a small town in South Africa’s Eastern Cape province, situated within the Buffalo City Metropolitan Municipality near East London.
  • C. Berlin
    Berlin is the capital and largest city of Germany, historically significant as a focal point of Cold War tensions and a major cultural, political, and economic center in Europe.
  • D. Berlin
    Berlin is a themed area in the Phantasialand amusement park that recreates the atmosphere and architecture of early 20th-century Berlin.
  • E. Berlin
    Berlin is an American new wave and synth-pop band best known for their 1986 hit power ballad "Take My Breath Away" from the film Top Gun.
  • 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_69e2455500788190b4b33030461f3bbd completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17c2f9ba48190996b4c3926728c03 completed April 29, 2026, 3:34 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b9e84691c8190acaf435ec6798c45 completed May 18, 2026, 11:19 p.m.
NEDg Description generation batch_6a0b9f1da4f88190bd9bea623d18d5b0 completed May 18, 2026, 11:22 p.m.
NED2 Entity disambiguation (via description) batch_6a0ba0fa26488190b2246d85b9b5a7b5 completed May 18, 2026, 11:30 p.m.
Created at: April 17, 2026, 3:29 p.m.