Triple
T15449742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sun Koshi |
E370117
|
entity |
| Predicate | confluenceWith |
P2416
|
FINISHED |
| Object |
Tama Koshi
Tama Koshi is a river in eastern Nepal that joins the Sun Koshi as one of the major tributaries of the Koshi river system.
|
E1157219
|
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: Tama Koshi | Statement: [Sun Koshi, confluenceWith, Tama Koshi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tama Koshi Context triple: [Sun Koshi, confluenceWith, Tama Koshi]
-
A.
Sun Koshi
Sun Koshi is a significant Himalayan river in Nepal known for its long, challenging whitewater rafting routes and contribution to the Koshi river system.
-
B.
Katayama Tōkuma
Katayama Tōkuma was a prominent Meiji-era Japanese architect known for pioneering Western-style imperial and public buildings in Japan.
-
C.
Kashiba
Kashiba is a city in Japan known for its residential communities and location in the northwestern part of Nara Prefecture, near the Osaka metropolitan area.
-
D.
Okinori Kaya
Okinori Kaya was a Japanese bureaucrat and politician who served as Finance Minister before and during World War II and was later convicted as a Class A war criminal.
-
E.
Takeo
Takeo is a Japanese given name commonly used for males and borne by various notable figures in fields such as politics, business, and the arts.
- 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: Tama Koshi Triple: [Sun Koshi, confluenceWith, Tama Koshi]
Generated description
Tama Koshi is a river in eastern Nepal that joins the Sun Koshi as one of the major tributaries of the Koshi river system.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tama Koshi Target entity description: Tama Koshi is a river in eastern Nepal that joins the Sun Koshi as one of the major tributaries of the Koshi river system.
-
A.
Sun Koshi
Sun Koshi is a significant Himalayan river in Nepal known for its long, challenging whitewater rafting routes and contribution to the Koshi river system.
-
B.
Katayama Tōkuma
Katayama Tōkuma was a prominent Meiji-era Japanese architect known for pioneering Western-style imperial and public buildings in Japan.
-
C.
Kashiba
Kashiba is a city in Japan known for its residential communities and location in the northwestern part of Nara Prefecture, near the Osaka metropolitan area.
-
D.
Okinori Kaya
Okinori Kaya was a Japanese bureaucrat and politician who served as Finance Minister before and during World War II and was later convicted as a Class A war criminal.
-
E.
Takeo
Takeo is a Japanese given name commonly used for males and borne by various notable figures in fields such as politics, business, and the arts.
- 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03ef9334c81908541e231b43eb012 |
completed | April 16, 2026, 1:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff21b1e9688190a283dbc552072ce0 |
completed | May 9, 2026, 11:59 a.m. |
| NEDg | Description generation | batch_69ff22b9c980819093e05036ba21eaf0 |
completed | May 9, 2026, 12:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff2339ae808190bf2d4676215399c0 |
completed | May 9, 2026, 12:06 p.m. |
Created at: April 10, 2026, 3:21 a.m.