Triple
T3485704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess Mako |
E73601
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Komuro
Komuro is the married surname of Japan’s former Princess Mako, adopted after her marriage to commoner Kei Komuro.
|
E364702
|
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: Komuro | Statement: [Princess Mako, familyName, Komuro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Komuro Context triple: [Princess Mako, familyName, Komuro]
-
A.
Takamikura
Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
-
B.
Kamitsumaki
Kamitsumaki is the first volume of the ancient Japanese chronicle Kojiki, focusing on Shinto creation myths and the age of the gods.
-
C.
Shimotsuki
Shimotsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk in late 1944.
-
D.
Moruya
Moruya is a coastal town in New South Wales, Australia, known for its scenic river setting, nearby beaches, and historic granite quarries.
-
E.
Marunouchi
Marunouchi is a central Tokyo business district known for its concentration of corporate headquarters, upscale offices, and proximity to Tokyo Station and the Imperial Palace.
- 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: Komuro Triple: [Princess Mako, familyName, Komuro]
Generated description
Komuro is the married surname of Japan’s former Princess Mako, adopted after her marriage to commoner Kei Komuro.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Komuro Target entity description: Komuro is the married surname of Japan’s former Princess Mako, adopted after her marriage to commoner Kei Komuro.
-
A.
Takamikura
Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
-
B.
Kamitsumaki
Kamitsumaki is the first volume of the ancient Japanese chronicle Kojiki, focusing on Shinto creation myths and the age of the gods.
-
C.
Shimotsuki
Shimotsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk in late 1944.
-
D.
Moruya
Moruya is a coastal town in New South Wales, Australia, known for its scenic river setting, nearby beaches, and historic granite quarries.
-
E.
Marunouchi
Marunouchi is a central Tokyo business district known for its concentration of corporate headquarters, upscale offices, and proximity to Tokyo Station and the Imperial Palace.
- 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_69ad85cca8d4819088494e9f3340fab5 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbb8f205c8190aa6f7484ebad14bb |
completed | March 8, 2026, 6:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b37e6202ec81908c9614102e618fb5 |
completed | March 13, 2026, 3:02 a.m. |
| NEDg | Description generation | batch_69b37ede876c8190ab8d4b595ebb1af2 |
completed | March 13, 2026, 3:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b37f5574b08190bdde80b47f2cb99c |
completed | March 13, 2026, 3:07 a.m. |
Created at: March 8, 2026, 3:18 p.m.