Triple
T7656279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tobu Skytree Line |
E173391
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Kita-Senju |
E207162
|
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: Kita-Senju | Statement: [Tobu Skytree Line, serves, Kita-Senju]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kita-Senju Context triple: [Tobu Skytree Line, serves, Kita-Senju]
-
A.
Kita-Senju
chosen
Kita-Senju is a major commercial and transportation hub in Tokyo, Japan, known for its busy railway station and shopping districts.
-
B.
Kasuga
Kasuga was a Japanese warship active in the late 19th century, notably serving in the Boshin War as part of the modern Imperial forces.
-
C.
Kasuga
Kasuga is a suburban city in Japan known for its residential communities and proximity to Fukuoka City on Kyushu Island.
-
D.
Kichijōji
Kichijōji is a popular Tokyo neighborhood known for its trendy shopping streets, vibrant dining and nightlife, and the expansive Inokashira Park.
-
E.
Shoin Jinja
Shoin Jinja is a Shinto shrine in Tokyo dedicated to the influential late-Edo period thinker and educator Yoshida Shōin.
- 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_69c69955517c819085bc715b96d304d2 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7018fcbb48190a479f2effd939a8e |
completed | March 27, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c89b05846c8190b49540aeae43dd9a |
completed | March 29, 2026, 3:22 a.m. |
Created at: March 27, 2026, 3:59 p.m.