Triple
T15109312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yamanote area |
E360869
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Kanda |
E577501
|
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: Kanda | Statement: [Yamanote area, hasPart, Kanda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kanda Context triple: [Yamanote area, hasPart, Kanda]
-
A.
Kanda
chosen
Kanda is a historic commercial and educational district in central Tokyo known for its bookstores, universities, and traditional shrines.
-
B.
Urakawa
Urakawa is a coastal town in Hokkaido, Japan, known for its horse breeding industry and scenic Pacific shoreline.
-
C.
Kuneē
Kuneē is the mythological helmet worn by Hades that grants its wearer invisibility in Greek mythology.
-
D.
Kōta
Kōta is a town in central Japan known for its manufacturing industries and location within Aichi Prefecture.
-
E.
Kamiyama
Kamiyama is a Japanese surname borne by various individuals, including artists, athletes, and public figures.
- 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_69d85a0491ec8190830960be8fafb994 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0058c04f481909deeac0271d961b6 |
completed | April 15, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69febfe2369881908c7ebbad412d9000 |
completed | May 9, 2026, 5:02 a.m. |
Created at: April 10, 2026, 3:05 a.m.