Triple
T16519781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 木曽川 |
E401286
|
entity |
| Predicate | hasTributary |
P415
|
FINISHED |
| Object |
揖斐川
揖斐川は岐阜県などを流れ伊勢湾へ注ぐ、日本の木曽三川の一つとして知られる河川である。
|
E1219004
|
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: 揖斐川 | Statement: [木曽川, hasTributary, 揖斐川]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 揖斐川 Context triple: [木曽川, hasTributary, 揖斐川]
-
A.
神田川
神田川 is a river in Tokyo, Japan, that flows through central districts such as Chiyoda and Bunkyo and is known for its historical and cultural significance.
-
B.
富士川
富士川は、山梨県と静岡県を流れ駿河湾に注ぐ、日本有数の急流として知られる大河川である。
-
C.
宇治川
宇治川は京都府南部を流れ、歴史的な合戦や宇治茶の産地として知られる日本の河川である。
-
D.
最上川
最上川は、山形県を中心に流れ日本三大急流の一つとして知られる東北地方の代表的な大河川です。
-
E.
野洲川
野洲川 is a river in Shiga Prefecture, Japan, that flows into Lake Biwa and is known for its role in local agriculture and flood control.
- 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: 揖斐川 Triple: [木曽川, hasTributary, 揖斐川]
Generated description
揖斐川は岐阜県などを流れ伊勢湾へ注ぐ、日本の木曽三川の一つとして知られる河川である。
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 揖斐川 Target entity description: 揖斐川は岐阜県などを流れ伊勢湾へ注ぐ、日本の木曽三川の一つとして知られる河川である。
-
A.
神田川
神田川 is a river in Tokyo, Japan, that flows through central districts such as Chiyoda and Bunkyo and is known for its historical and cultural significance.
-
B.
富士川
富士川は、山梨県と静岡県を流れ駿河湾に注ぐ、日本有数の急流として知られる大河川である。
-
C.
宇治川
宇治川は京都府南部を流れ、歴史的な合戦や宇治茶の産地として知られる日本の河川である。
-
D.
最上川
最上川は、山形県を中心に流れ日本三大急流の一つとして知られる東北地方の代表的な大河川です。
-
E.
野洲川
野洲川 is a river in Shiga Prefecture, Japan, that flows into Lake Biwa and is known for its role in local agriculture and flood control.
- 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e7f8a1481909fe6b3c16a72059b |
completed | April 18, 2026, 7:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a006088fe4881909e5b691743157700 |
completed | May 10, 2026, 10:40 a.m. |
| NEDg | Description generation | batch_6a006486cf4c8190a4f1b096f70b016b |
completed | May 10, 2026, 10:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0064e3388c8190bb477fadf51469e8 |
completed | May 10, 2026, 10:58 a.m. |
Created at: April 10, 2026, 5:14 a.m.