Triple

T2814308
Position Surface form Disambiguated ID Type / Status
Subject Kantō region E54245 entity
Predicate containsMajorCity P316 FINISHED
Object Mito
Mito is the capital city of Ibaraki Prefecture in Japan’s Kantō region, known for its historic Kairakuen Garden and cultural heritage.
 E300703 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: Mito | Statement: [Kantō region, containsMajorCity, Mito]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mito
Context triple: [Kantō region, containsMajorCity, Mito]
  • A. Mitino
    Mitino is a Moscow Metro station serving the Mitino District in the northwestern part of the city.
  • B. Kish
    Kish is a Benjaminite figure in the Hebrew Bible best known as the father of Israel’s first king, Saul.
  • C. Kish
    Kish was an important ancient Sumerian city-state in Mesopotamia, often associated with early kingship traditions and political power in the region.
  • D. Mosta
    Mosta is a town in central Malta best known for its impressive Rotunda church, which has one of the largest unsupported domes in the world.
  • E. Kamen
    Kamen is a surname most prominently associated with American inventor and entrepreneur Dean Kamen, known for creating the Segway and numerous medical devices.
  • 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: Mito
Triple: [Kantō region, containsMajorCity, Mito]
Generated description
Mito is the capital city of Ibaraki Prefecture in Japan’s Kantō region, known for its historic Kairakuen Garden and cultural heritage.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mito
Target entity description: Mito is the capital city of Ibaraki Prefecture in Japan’s Kantō region, known for its historic Kairakuen Garden and cultural heritage.
  • A. Mitino
    Mitino is a Moscow Metro station serving the Mitino District in the northwestern part of the city.
  • B. Kish
    Kish is a Benjaminite figure in the Hebrew Bible best known as the father of Israel’s first king, Saul.
  • C. Kish
    Kish was an important ancient Sumerian city-state in Mesopotamia, often associated with early kingship traditions and political power in the region.
  • D. Mosta
    Mosta is a town in central Malta best known for its impressive Rotunda church, which has one of the largest unsupported domes in the world.
  • E. Kamen
    Kamen is a surname most prominently associated with American inventor and entrepreneur Dean Kamen, known for creating the Segway and numerous medical devices.
  • 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_69ab49de0af08190b3da69683be1e728 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde4ba34c819085a336498fc326b0 completed March 7, 2026, 8:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69afce9f964081909e422aaf1f026dbb completed March 10, 2026, 7:56 a.m.
NEDg Description generation batch_69afcf12e3a0819098f28d31434a0c5f completed March 10, 2026, 7:58 a.m.
NED2 Entity disambiguation (via description) batch_69afcf9c2d308190b111aa8038c9227a completed March 10, 2026, 8 a.m.
Created at: March 6, 2026, 9:59 p.m.