Triple
T3364912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chiyoda |
E70810
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Sumida |
E34202
|
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: Sumida | Statement: [Chiyoda, borders, Sumida]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sumida Context triple: [Chiyoda, borders, Sumida]
-
A.
Sumida
chosen
Sumida is a special ward in Tokyo, Japan, known for landmarks such as the Tokyo Skytree and its traditional shitamachi neighborhoods.
-
B.
Sumida River
The Sumida River is a historically significant river flowing through central Tokyo, known for its scenic bridges, cherry blossoms, and cultural prominence in Japanese art and literature.
-
C.
Meguro River
The Meguro River is a well-known urban river in Tokyo, Japan, famous for its picturesque cherry blossom-lined banks that attract many visitors during spring.
-
D.
Takanawa
Takanawa is an upscale residential and commercial district in Minato, Tokyo, known for its luxury hotels, embassies, and proximity to major transport hubs like Shinagawa Station.
-
E.
Arakawa River
The Arakawa River is a major river in the Tokyo region of Japan, known for its extensive flood control systems and role in shaping the urban landscape.
- 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_69ad85a729d48190afd789cd8417f289 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb28643f48190b78b0222f8323344 |
completed | March 8, 2026, 5:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b334332ce88190b898894286c166c2 |
completed | March 12, 2026, 9:46 p.m. |
Created at: March 8, 2026, 3:13 p.m.