Triple
T16537205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suginami |
E401722
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Koenji |
E853001
|
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: Koenji | Statement: [Suginami, contains, Koenji]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Koenji Context triple: [Suginami, contains, Koenji]
-
A.
Koenji
chosen
Koenji is a lively Tokyo neighborhood known for its vintage clothing shops, underground music scene, and numerous small bars and eateries.
-
B.
Kanamecho
Kanamecho is a neighborhood in Tokyo known for its residential character, local shopping streets, and convenient access via the Tokyo Metro Yurakucho and Fukutoshin lines.
-
C.
Kōtō
Kōtō is a special ward in eastern Tokyo, Japan, known for its mix of residential neighborhoods, waterfront areas, and commercial districts.
-
D.
Kamitabashi
Kamitabashi is a residential neighborhood located in the Kita ward of Tokyo, Japan.
-
E.
Kagurazaka
Kagurazaka is a historic neighborhood in central Tokyo known for its narrow cobblestone streets, traditional ryotei restaurants, and blend of old geisha district charm with modern boutiques and cafes.
- 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_69d88384bc30819084229e7dcdc39a41 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e34559ca948190a9eb810b9b3be079 |
completed | April 18, 2026, 8:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0067aafee48190a0652fb4fac04a5b |
completed | May 10, 2026, 11:10 a.m. |
Created at: April 10, 2026, 5:15 a.m.