Triple

T13206874
Position Surface form Disambiguated ID Type / Status
Subject Mogami River E314387 entity
Predicate mouthLocation P417 FINISHED
Object Sakata
Sakata is a coastal city in Yamagata Prefecture, Japan, known historically as a prominent port and trading center on the Sea of Japan.
 E1110900 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: Sakata | Statement: [Mogami River, mouthLocation, Sakata]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sakata
Context triple: [Mogami River, mouthLocation, Sakata]
  • A. Sakata
    Sakata is a Japanese surname borne by various notable individuals in fields such as physics, sports, and entertainment.
  • B. Takaishi
    Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
  • C. Sakae
    Sakae is a major downtown commercial and entertainment district in Nagoya, Japan, known for its shopping, nightlife, and landmark attractions.
  • D. Wakatsuki
    Wakatsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk during late-war Pacific naval operations.
  • E. Saito
    Saito is a Japanese surname commonly borne by notable figures in fields such as politics, sports, and the arts.
  • 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: Sakata
Triple: [Mogami River, mouthLocation, Sakata]
Generated description
Sakata is a coastal city in Yamagata Prefecture, Japan, known historically as a prominent port and trading center on the Sea of Japan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sakata
Target entity description: Sakata is a coastal city in Yamagata Prefecture, Japan, known historically as a prominent port and trading center on the Sea of Japan.
  • A. Sakata
    Sakata is a Japanese surname borne by various notable individuals in fields such as physics, sports, and entertainment.
  • B. Takaishi
    Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
  • C. Sakae
    Sakae is a major downtown commercial and entertainment district in Nagoya, Japan, known for its shopping, nightlife, and landmark attractions.
  • D. Wakatsuki
    Wakatsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk during late-war Pacific naval operations.
  • E. Saito
    Saito is a Japanese surname commonly borne by notable figures in fields such as politics, sports, and the arts.
  • 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_69d806aee7308190b70a237ba2a6e3e1 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c9cb7ac819095cff8699993c419 completed April 10, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda8fd6f5081908de9a9e3df28a8ea completed May 8, 2026, 9:12 a.m.
NEDg Description generation batch_69fdb187bf1c819098675af82ee70b5b completed May 8, 2026, 9:48 a.m.
NED2 Entity disambiguation (via description) batch_69fdb27fd90881909a938ecd227873b4 completed May 8, 2026, 9:53 a.m.
Created at: April 9, 2026, 9:17 p.m.