Triple

T16078477
Position Surface form Disambiguated ID Type / Status
Subject Tasuku Honjo E390036 entity
Predicate givenName P17 FINISHED
Object Tasuku
Tasuku is a Japanese given name most famously borne by immunologist Tasuku Honjo, a Nobel Prize laureate recognized for his work on cancer immunotherapy.
E1192599 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: Tasuku | Statement: [Tasuku Honjo, givenName, Tasuku]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tasuku
Context triple: [Tasuku Honjo, givenName, Tasuku]
  • A. Sumio
    Sumio is a Japanese physicist best known for his pioneering discovery and characterization of carbon nanotubes.
  • B. Kurō
    Kurō is an honorific name historically associated with the famed Japanese military commander Minamoto no Yoshitsune of the late Heian period.
  • C. Machimura
    Machimura is a Japanese surname most notably associated with Nobutaka Machimura, a prominent Liberal Democratic Party politician and former foreign minister of Japan.
  • D. Seppa
    Seppa is a town in the East Kameng district of Arunachal Pradesh in northeastern India, serving as an administrative and cultural center in the Himalayan foothills.
  • E. Takaishi
    Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
  • 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: Tasuku
Triple: [Tasuku Honjo, givenName, Tasuku]
Generated description
Tasuku is a Japanese given name most famously borne by immunologist Tasuku Honjo, a Nobel Prize laureate recognized for his work on cancer immunotherapy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tasuku
Target entity description: Tasuku is a Japanese given name most famously borne by immunologist Tasuku Honjo, a Nobel Prize laureate recognized for his work on cancer immunotherapy.
  • A. Sumio
    Sumio is a Japanese physicist best known for his pioneering discovery and characterization of carbon nanotubes.
  • B. Kurō
    Kurō is an honorific name historically associated with the famed Japanese military commander Minamoto no Yoshitsune of the late Heian period.
  • C. Machimura
    Machimura is a Japanese surname most notably associated with Nobutaka Machimura, a prominent Liberal Democratic Party politician and former foreign minister of Japan.
  • D. Seppa
    Seppa is a town in the East Kameng district of Arunachal Pradesh in northeastern India, serving as an administrative and cultural center in the Himalayan foothills.
  • E. Takaishi
    Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
  • 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_69d86daf32ec8190a8c0466c8f49c3c0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e183c401a881908fcb0b753d2dfc8a completed April 17, 2026, 12:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffe48907148190ab04520717141788 completed May 10, 2026, 1:51 a.m.
NEDg Description generation batch_69ffe67043588190864864d40956682b completed May 10, 2026, 1:59 a.m.
NED2 Entity disambiguation (via description) batch_69ffe6f510cc8190b6b8c46c0356d36a completed May 10, 2026, 2:01 a.m.
Created at: April 10, 2026, 4:57 a.m.