Triple
T2390628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keio Medical Science Prize |
E48932
|
entity |
| Predicate | notableLaureate |
P1618
|
FINISHED |
| Object |
Tasuku Honjo
Tasuku Honjo is a Japanese immunologist and Nobel laureate renowned for discovering the PD-1 protein, which led to groundbreaking cancer immunotherapy treatments.
|
E390036
|
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 Honjo | Statement: [Keio Medical Science Prize, notableLaureate, Tasuku Honjo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tasuku Honjo Context triple: [Keio Medical Science Prize, notableLaureate, Tasuku Honjo]
-
A.
Hatazō Adachi
Hatazō Adachi was a Japanese general of the Imperial Japanese Army during World War II, best known for commanding forces in the Pacific theater.
-
B.
Makoto Uchida
Makoto Uchida is a Japanese automotive executive who serves as the chief executive officer of Nissan Motor Co.
-
C.
Makoto Yamashita
Makoto Yamashita is a Japanese politician serving as the governor of Nara Prefecture.
-
D.
Hirofumi Hirano
Hirofumi Hirano is a Japanese politician who has held senior leadership roles in major opposition parties and served in the national legislature.
-
E.
Takatoshi Nishiwaki
Takatoshi Nishiwaki is a Japanese politician serving as the governor of Kyoto Prefecture.
- 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 Honjo Triple: [Keio Medical Science Prize, notableLaureate, Tasuku Honjo]
Generated description
Tasuku Honjo is a Japanese immunologist and Nobel laureate renowned for discovering the PD-1 protein, which led to groundbreaking cancer immunotherapy treatments.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tasuku Honjo Target entity description: Tasuku Honjo is a Japanese immunologist and Nobel laureate renowned for discovering the PD-1 protein, which led to groundbreaking cancer immunotherapy treatments.
-
A.
Hatazō Adachi
Hatazō Adachi was a Japanese general of the Imperial Japanese Army during World War II, best known for commanding forces in the Pacific theater.
-
B.
Makoto Uchida
Makoto Uchida is a Japanese automotive executive who serves as the chief executive officer of Nissan Motor Co.
-
C.
Makoto Yamashita
Makoto Yamashita is a Japanese politician serving as the governor of Nara Prefecture.
-
D.
Hirofumi Hirano
Hirofumi Hirano is a Japanese politician who has held senior leadership roles in major opposition parties and served in the national legislature.
-
E.
Takatoshi Nishiwaki
Takatoshi Nishiwaki is a Japanese politician serving as the governor of Kyoto Prefecture.
- 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_69a88aa5f63081908d07fd302029fcbd |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc87457388190822d5506327db8f2 |
completed | March 7, 2026, 6:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4fad35a0c8190a07cc7877fbfec04 |
completed | March 14, 2026, 6:06 a.m. |
| NEDg | Description generation | batch_69b4fc1d144881908affcdae84a3c395 |
completed | March 14, 2026, 6:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4fc942b588190985b191376289258 |
completed | March 14, 2026, 6:13 a.m. |
Created at: March 4, 2026, 7:57 p.m.