Triple
T13452661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meitetsu |
E320648
|
entity |
| Predicate | focusCity |
P164
|
FINISHED |
| Object | Toyohashi |
—
|
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: Toyohashi | Statement: [Meitetsu, focusCity, Toyohashi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toyohashi Context triple: [Meitetsu, focusCity, Toyohashi]
-
A.
Toyohashi
chosen
Toyohashi is a city in Aichi Prefecture, Japan, known as a regional commercial and transportation hub on the Pacific coast of central Honshu.
-
B.
Yokkaichi
Yokkaichi is an industrial port city in central Japan known for its petrochemical complexes and role as a major manufacturing hub.
-
C.
Nagahama
Nagahama is a historic lakeside city in central Japan known for its preserved Edo-period streets, Nagahama Castle, and scenic location on the northeastern shore of Lake Biwa.
-
D.
Kishiwada
Kishiwada is a coastal city in southern Osaka Prefecture, Japan, best known for its historic castle and the lively Kishiwada Danjiri Matsuri festival.
-
E.
Kurashiki
Kurashiki is a historic industrial and canal city in Okayama Prefecture, Japan, known for its well-preserved Edo-period merchant quarter and traditional warehouses.
- 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_69d80761e6cc8190a90c844589998ecc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaefae85481909e6a59797cbb25e7 |
completed | April 12, 2026, 2:40 p.m. |
Created at: April 9, 2026, 9:41 p.m.