Triple
T7656300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tobu Skytree Line |
E173391
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Soka |
E255181
|
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: Soka | Statement: [Tobu Skytree Line, serves, Soka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Soka Context triple: [Tobu Skytree Line, serves, Soka]
-
A.
Soka
chosen
Soka is a city in Japan known for its location in Saitama Prefecture just north of Tokyo and its traditional rice crackers called "Soka senbei."
-
B.
Sodeke
Sodeke was a prominent 19th-century Egba leader and war chief who played a central role in uniting the Egba people and establishing the city of Abeokuta in present-day Nigeria.
-
C.
Sankashū
Sankashū is a renowned anthology of waka poetry by the Japanese poet-monk Saigyō, celebrated for its deeply reflective and nature-focused verse from the late Heian period.
-
D.
Sikiajhora
Sikiajhora is a forest stream and wetland area within West Bengal’s Buxa Tiger Reserve, known for its rich biodiversity and boat-based wildlife viewing.
-
E.
Kōdō
Kōdō is the Lecture Hall of the historic Tōshōdai-ji Buddhist temple in Nara, Japan, used for religious teachings and ceremonial gatherings.
- 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.