Triple
T905623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empress Kōjun |
E19540
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object |
Kōjun Kōgō
Kōjun Kōgō was the Empress consort of Japan as the wife of Emperor Shōwa (Hirohito) and the mother of Emperor Emeritus Akihito.
|
E187079
|
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: Kōjun Kōgō | Statement: [Empress Kōjun, alsoKnownAs, Kōjun Kōgō]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kōjun Kōgō Context triple: [Empress Kōjun, alsoKnownAs, Kōjun Kōgō]
-
A.
Yokoi Shōnan
Yokoi Shōnan was a late Edo and early Meiji-era Japanese political thinker and reformist samurai known for advocating Western-style modernization and national strengthening.
-
B.
Mutaguchi Renya
Mutaguchi Renya was a Japanese general best known for commanding the ill-fated Imphal offensive in Burma during World War II.
-
C.
Saburō Kurusu
Saburō Kurusu was a Japanese diplomat best known for his role in U.S.-Japan negotiations immediately before the attack on Pearl Harbor.
-
D.
Koji Sato
Koji Sato is a Japanese automotive executive who serves as the president and CEO of Toyota Motor Corporation.
-
E.
Yamaguchi Naoyoshi
Yamaguchi Naoyoshi was a Japanese statesman of the early Meiji era who took part in Japan’s modernization efforts, including its landmark diplomatic and study tour abroad.
- 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: Kōjun Kōgō Triple: [Empress Kōjun, alsoKnownAs, Kōjun Kōgō]
Generated description
Kōjun Kōgō was the Empress consort of Japan as the wife of Emperor Shōwa (Hirohito) and the mother of Emperor Emeritus Akihito.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kōjun Kōgō Target entity description: Kōjun Kōgō was the Empress consort of Japan as the wife of Emperor Shōwa (Hirohito) and the mother of Emperor Emeritus Akihito.
-
A.
Yokoi Shōnan
Yokoi Shōnan was a late Edo and early Meiji-era Japanese political thinker and reformist samurai known for advocating Western-style modernization and national strengthening.
-
B.
Mutaguchi Renya
Mutaguchi Renya was a Japanese general best known for commanding the ill-fated Imphal offensive in Burma during World War II.
-
C.
Saburō Kurusu
Saburō Kurusu was a Japanese diplomat best known for his role in U.S.-Japan negotiations immediately before the attack on Pearl Harbor.
-
D.
Koji Sato
Koji Sato is a Japanese automotive executive who serves as the president and CEO of Toyota Motor Corporation.
-
E.
Yamaguchi Naoyoshi
Yamaguchi Naoyoshi was a Japanese statesman of the early Meiji era who took part in Japan’s modernization efforts, including its landmark diplomatic and study tour abroad.
- 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_69a4939e889c8190ac148b3ac1a7f90b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2caf4088190ab05b22531ecec43 |
completed | March 1, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad606f1c008190adca6fa6f0d6cd66 |
completed | March 8, 2026, 11:41 a.m. |
| NEDg | Description generation | batch_69ad61ff65b881909009c230780a146e |
completed | March 8, 2026, 11:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad62ec3a80819085fef1c378b9abdc |
completed | March 8, 2026, 11:52 a.m. |
Created at: March 1, 2026, 7:39 p.m.