Triple
T3014268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naniwa-ku |
E82297
|
entity |
| Predicate | hasNeighbouringWard |
P45005
|
FINISHED |
| Object | Nishi-ku |
E364559
|
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: Nishi-ku | Statement: [Naniwa-ku, hasNeighbouringWard, Nishi-ku]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nishi-ku Context triple: [Naniwa-ku, hasNeighbouringWard, Nishi-ku]
-
A.
Nishi-ku
chosen
Nishi-ku is a ward in Fukuoka, Japan, known for its coastal areas, residential neighborhoods, and access to both urban amenities and natural scenery.
-
B.
Nishi-ku
Nishi-ku is a central ward of Yokohama, Japan, known as a major commercial and business district that includes the Minato Mirai 21 waterfront area.
-
C.
Higashi-ku
Higashi-ku is a ward in the city of Fukuoka, Japan, known for its coastal location, residential areas, and educational institutions.
-
D.
Miyagino-ku
Miyagino-ku is one of the administrative wards of Sendai, Japan, known for its mix of residential areas, commercial facilities, and transportation hubs.
-
E.
Nakahara-ku
Nakahara-ku is one of the administrative wards of Kawasaki City in Kanagawa Prefecture, Japan, known as a residential and commercial area within the Greater Tokyo metropolitan region.
- 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_69ad8b1eb53481908c39bbcd1ec104b2 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9e11c4188190a3ae8fd0cbd8c2c0 |
completed | March 8, 2026, 4:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bd567a48b881908e4bfec70943eb60 |
completed | March 20, 2026, 2:15 p.m. |
Created at: March 8, 2026, 3 p.m.