Triple
T3517838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ume Sami |
E74349
|
entity |
| Predicate | spokenAlong |
P24200
|
FINISHED |
| Object | Ume River |
E246381
|
NE FINISHED |
How this triple was built (2 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: Ume River | Statement: [Ume Sami, spokenAlong, Ume River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ume River Context triple: [Ume Sami, spokenAlong, Ume River]
-
A.
Ume River
chosen
The Ume River is a significant river in northern Sweden that flows through Västerbotten County and the city of Umeå before emptying into the Gulf of Bothnia.
-
B.
Tenryu River
The Tenryu River is a major river in central Japan that flows through Nagano and Shizuoka Prefectures before emptying into the Pacific Ocean, known for its strong currents and scenic gorges.
-
C.
Mukogawa River
The Mukogawa River is a prominent river in Japan’s Hyōgo Prefecture that flows through cities such as Nishinomiya before emptying into Osaka Bay.
-
D.
Shinano River
The Shinano River is Japan’s longest river, flowing through central Honshu before emptying into the Sea of Japan.
-
E.
Kamogawa River
The Kamogawa River is a prominent river flowing through Kyoto, Japan, known for its scenic banks lined with traditional teahouses, restaurants, and popular walking paths.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ad85cfb5c881909c9a2edd9d6043cc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc32f90081908960acb3e94402be |
completed | March 8, 2026, 6:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bda3f5a8a88190a494a9338c01962a |
completed | March 20, 2026, 7:45 p.m. |
Created at: March 8, 2026, 3:19 p.m.