Triple
T12420092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Honjo |
E296744
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Ryogoku |
E188824
|
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: Ryogoku | Statement: [Honjo, near, Ryogoku]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ryogoku Context triple: [Honjo, near, Ryogoku]
-
A.
Ryōgoku
chosen
Ryōgoku is a historic district in Tokyo best known as the heart of professional sumo wrestling and home to the Ryōgoku Kokugikan arena.
-
B.
Komagome
Komagome is a residential and commercial neighborhood in Tokyo known for its traditional atmosphere, historic temples, and the renowned Rikugien Garden.
-
C.
Bunkyō
Bunkyō is a central Tokyo ward known for its universities, historic temples, and quiet residential neighborhoods.
-
D.
Yanaka
Yanaka is a traditional, temple-filled neighborhood in Tokyo known for its preserved old-town atmosphere, narrow lanes, and historic cemetery.
-
E.
Sumida Park
Sumida Park is a riverside public park in Tokyo renowned for its cherry blossoms and scenic views along the Sumida River.
- 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_69d6ada0640c81908c061d7fb3d47786 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d6efd748190a5d9396a343e41e1 |
completed | April 10, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f634933b9881909fd592ede7c3e49c |
completed | May 2, 2026, 5:29 p.m. |
Created at: April 8, 2026, 9:55 p.m.