Triple
T7401676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Biwa |
E170762
|
entity |
| Predicate | hasCityOnShore |
P969
|
FINISHED |
| Object | Nagahama |
E390811
|
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: Nagahama | Statement: [Lake Biwa, hasCityOnShore, Nagahama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nagahama Context triple: [Lake Biwa, hasCityOnShore, Nagahama]
-
A.
Nagahama
chosen
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.
-
B.
Neyagawa
Neyagawa is a city in Osaka Prefecture, Japan, known as a residential and commercial suburb within the Osaka metropolitan area.
-
C.
Toyohashi
Toyohashi is a city in Aichi Prefecture, Japan, known as a regional commercial and transportation hub on the Pacific coast of central Honshu.
-
D.
Yokkaichi
Yokkaichi is an industrial port city in central Japan known for its petrochemical complexes and role as a major manufacturing hub.
-
E.
Maibara
Maibara is a city in Shiga Prefecture, Japan, known as a regional transportation hub with a Shinkansen station and scenic views of nearby Lake Biwa and surrounding mountains.
- 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_69c68a5f04188190ac266569c9280347 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f26d6d6081909c7272a9ccae0d97 |
completed | March 27, 2026, 9:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e343941ae481909489cf7a4abdba68 |
completed | April 18, 2026, 8:40 a.m. |
Created at: March 27, 2026, 3:10 p.m.