Triple
T1595911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shiga |
E34281
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Yasu
Yasu is a Japanese city located in Shiga Prefecture, known for its blend of residential areas, local industry, and proximity to Lake Biwa.
|
E295843
|
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: Yasu | Statement: [Shiga, hasCity, Yasu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yasu Context triple: [Shiga, hasCity, Yasu]
-
A.
Yukio
Yukio is a Japanese given name commonly used for males and borne by several notable figures in politics, arts, and entertainment.
-
B.
Kentarō
Kentarō is a Japanese given name commonly used for males, often associated with traditional or strong-sounding name combinations.
-
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.
Takanami
Takanami was a Japanese destroyer of the Imperial Japanese Navy during World War II, notable for being sunk in the Battle of Tassafaronga in 1942.
-
E.
Shinpei
Shinpei is a Japanese given name commonly used for males and borne by various notable figures in politics, arts, and entertainment.
- 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: Yasu Triple: [Shiga, hasCity, Yasu]
Generated description
Yasu is a Japanese city located in Shiga Prefecture, known for its blend of residential areas, local industry, and proximity to Lake Biwa.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Yasu Target entity description: Yasu is a Japanese city located in Shiga Prefecture, known for its blend of residential areas, local industry, and proximity to Lake Biwa.
-
A.
Yukio
Yukio is a Japanese given name commonly used for males and borne by several notable figures in politics, arts, and entertainment.
-
B.
Kentarō
Kentarō is a Japanese given name commonly used for males, often associated with traditional or strong-sounding name combinations.
-
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.
Takanami
Takanami was a Japanese destroyer of the Imperial Japanese Navy during World War II, notable for being sunk in the Battle of Tassafaronga in 1942.
-
E.
Shinpei
Shinpei is a Japanese given name commonly used for males and borne by various notable figures in politics, arts, and entertainment.
- 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_69a885fdcb9c819081ce6f0b8cd477dd |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9092ccb388190b2f3ed86b3853651 |
completed | March 5, 2026, 4:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afbba3f0ec81909c73a0e3a0e0d3f2 |
completed | March 10, 2026, 6:35 a.m. |
| NEDg | Description generation | batch_69afbcd294cc819094e13bd85266c3cc |
completed | March 10, 2026, 6:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afbd452e1c8190a3ee9eaf642e80a0 |
completed | March 10, 2026, 6:42 a.m. |
Created at: March 4, 2026, 7:27 p.m.