Triple
T23469539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ningyōchō |
E569188
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Hamacho |
—
|
NE NERFINISHED |
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: Hamacho | Statement: [Ningyōchō, near, Hamacho]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hamacho Context triple: [Ningyōchō, near, Hamacho]
-
A.
Tajōmaru
Tajōmaru is the notorious bandit whose conflicting testimonies drive the plot and themes of truth and perception in Ryūnosuke Akutagawa’s short story "In a Grove."
-
B.
Hamachō
chosen
Hamachō is a neighborhood in Chūō ward, central Tokyo, known for its mix of residential areas, local businesses, and proximity to the Nihonbashi district.
-
C.
Honancho
Honancho is a neighborhood in Tokyo, Japan, known as a residential area with convenient access to central city districts via the Tokyo Metro Marunouchi Line.
-
D.
Sachio
Sachio is a Japanese masculine given name that can be written with various kanji characters and is borne by multiple notable individuals.
-
E.
Saiko
Saiko is the romanized name of Lake Sai, one of the scenic Fuji Five Lakes near Mount Fuji in Japan.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2458ebd808190b3298163132cfb0b |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a6feb5688190ad4ce42fc9590adb |
completed | April 29, 2026, 6:36 a.m. |
Created at: April 17, 2026, 5:54 p.m.