Triple

T11081491
Position Surface form Disambiguated ID Type / Status
Subject Lake Sai E262003 entity
Predicate hasRomanizedName P2508 FINISHED
Object Saiko
Saiko is the romanized name of Lake Sai, one of the scenic Fuji Five Lakes near Mount Fuji in Japan.
 E903775 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: Saiko | Statement: [Lake Sai, hasRomanizedName, Saiko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Saiko
Context triple: [Lake Sai, hasRomanizedName, Saiko]
  • A. Tokashiki
    Tokashiki is a small island municipality in Okinawa Prefecture, Japan, known for its clear waters, coral reefs, and popular diving and snorkeling spots within the Kerama Islands.
  • B. Sadahito
    Sadahito was the personal name of Emperor Shirakawa, a Japanese emperor of the late 11th and early 12th centuries known for initiating the cloistered rule system.
  • C. Shin-Koiwa
    Shin-Koiwa is a residential and commercial neighborhood in Tokyo known for its busy railway station, local shopping streets, and traditional shitamachi atmosphere.
  • D. Shinaki
    Shinaki is an alternative name for the Shina people, an ethnic group primarily inhabiting the mountainous regions of northern Pakistan and parts of India.
  • E. Masaru
    Masaru is a Japanese given name commonly used for males and borne by various notable figures in fields such as technology, sports, and entertainment.
  • 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: Saiko
Triple: [Lake Sai, hasRomanizedName, Saiko]
Generated description
Saiko is the romanized name of Lake Sai, one of the scenic Fuji Five Lakes near Mount Fuji in Japan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Saiko
Target entity description: Saiko is the romanized name of Lake Sai, one of the scenic Fuji Five Lakes near Mount Fuji in Japan.
  • A. Tokashiki
    Tokashiki is a small island municipality in Okinawa Prefecture, Japan, known for its clear waters, coral reefs, and popular diving and snorkeling spots within the Kerama Islands.
  • B. Sadahito
    Sadahito was the personal name of Emperor Shirakawa, a Japanese emperor of the late 11th and early 12th centuries known for initiating the cloistered rule system.
  • C. Shin-Koiwa
    Shin-Koiwa is a residential and commercial neighborhood in Tokyo known for its busy railway station, local shopping streets, and traditional shitamachi atmosphere.
  • D. Shinaki
    Shinaki is an alternative name for the Shina people, an ethnic group primarily inhabiting the mountainous regions of northern Pakistan and parts of India.
  • E. Masaru
    Masaru is a Japanese given name commonly used for males and borne by various notable figures in fields such as technology, sports, and entertainment.
  • 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_69d6aa9983c08190b0ef61603b69feac completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d799985650819089b2c0f35a212414 completed April 9, 2026, 12:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3e789d7248190a40de0bdda539f45 completed April 18, 2026, 8:20 p.m.
NEDg Description generation batch_69e3f2c889dc81909a04c1db0509e3d9 completed April 18, 2026, 9:08 p.m.
NED2 Entity disambiguation (via description) batch_69e3f4746dbc8190a0e28202ad5e6b4f completed April 18, 2026, 9:15 p.m.
Created at: April 8, 2026, 9:27 p.m.