Triple

T3365951
Position Surface form Disambiguated ID Type / Status
Subject Kido Takayoshi E70835 entity
Predicate familyName P18 FINISHED
Object Kido
Kido is a Japanese surname most famously borne by Kido Takayoshi, a key samurai statesman of the Meiji Restoration.
 E351836 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: Kido | Statement: [Kido Takayoshi, familyName, Kido]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kido
Context triple: [Kido Takayoshi, familyName, Kido]
  • A. Son Kitei
    Son Kitei was the Korean-born marathon runner who won the gold medal for Japan at the 1936 Berlin Olympics, later symbolizing the complex colonial history between Korea and Japan.
  • B. Kyodai
    Kyodai is the common abbreviated name for Kyoto University, one of Japan’s most prestigious national research universities.
  • C. Kintomo Mushakoji
    Kintomo Mushakoji was a Japanese diplomat who served as a key representative of Japan’s government in the 1930s, notably involved in its alignment with Axis powers.
  • D. Kibushi
    Kibushi is a Bantu language spoken primarily in Mayotte, where it serves as one of the island’s main regional languages.
  • E. Kanuma
    Kanuma is a regional harvest festival celebrated mainly in Andhra Pradesh and Telangana as part of the multi-day Makar Sankranti festivities, focusing on cattle worship and agricultural prosperity.
  • 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: Kido
Triple: [Kido Takayoshi, familyName, Kido]
Generated description
Kido is a Japanese surname most famously borne by Kido Takayoshi, a key samurai statesman of the Meiji Restoration.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kido
Target entity description: Kido is a Japanese surname most famously borne by Kido Takayoshi, a key samurai statesman of the Meiji Restoration.
  • A. Son Kitei
    Son Kitei was the Korean-born marathon runner who won the gold medal for Japan at the 1936 Berlin Olympics, later symbolizing the complex colonial history between Korea and Japan.
  • B. Kyodai
    Kyodai is the common abbreviated name for Kyoto University, one of Japan’s most prestigious national research universities.
  • C. Kintomo Mushakoji
    Kintomo Mushakoji was a Japanese diplomat who served as a key representative of Japan’s government in the 1930s, notably involved in its alignment with Axis powers.
  • D. Kibushi
    Kibushi is a Bantu language spoken primarily in Mayotte, where it serves as one of the island’s main regional languages.
  • E. Kanuma
    Kanuma is a regional harvest festival celebrated mainly in Andhra Pradesh and Telangana as part of the multi-day Makar Sankranti festivities, focusing on cattle worship and agricultural prosperity.
  • 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_69ad85a729d48190afd789cd8417f289 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb287a30c8190b4c40091675c94fb completed March 8, 2026, 5:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69b325500eac8190b6f43864af8bda6c completed March 12, 2026, 8:42 p.m.
NEDg Description generation batch_69b329016c7c819098b494ae5d712036 completed March 12, 2026, 8:58 p.m.
NED2 Entity disambiguation (via description) batch_69b329aca800819091f287a2f00557a2 completed March 12, 2026, 9:01 p.m.
Created at: March 8, 2026, 3:13 p.m.