Triple
T7496960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tobu Nikko Line |
E177154
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Nikko |
E253811
|
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: Nikko | Statement: [Tobu Nikko Line, connectsTo, Nikko]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nikko Context triple: [Tobu Nikko Line, connectsTo, Nikko]
-
A.
Nikko
chosen
Nikko is a historic Japanese city in Tochigi Prefecture renowned for its ornate UNESCO-listed shrines, temples, and scenic mountainous landscapes.
-
B.
Hakone
Hakone is a popular hot spring resort town in Japan known for its views of Mount Fuji, scenic lakes, and traditional ryokan inns.
-
C.
Fujikawaguchiko
Fujikawaguchiko is a Japanese resort town in Yamanashi Prefecture known for its views of Mount Fuji and Lake Kawaguchi, hot springs, and access to Fuji Five Lakes.
-
D.
Nagaoka-kyō
Nagaoka-kyō was an ancient Japanese imperial capital established in the late 8th century, serving briefly as the political center before the court moved to Heian-kyō (Kyoto).
-
E.
Kamikochi
Kamikochi is a scenic highland valley in Japan’s Northern Alps renowned for its pristine river, mountain views, and popular hiking trails.
- 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_69c69f2583808190bd1a4936c42a5815 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f5963d98819098275b161848d2d4 |
completed | March 27, 2026, 9:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c846043ed48190b6fa45ed0e70b4d3 |
completed | March 28, 2026, 9:20 p.m. |
Created at: March 27, 2026, 3:44 p.m.