Triple
T6641339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo Wan Aqua-Line Expressway |
E150592
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Kisarazu |
E790089
|
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: Kisarazu | Statement: [Tokyo Wan Aqua-Line Expressway, connects, Kisarazu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kisarazu Context triple: [Tokyo Wan Aqua-Line Expressway, connects, Kisarazu]
-
A.
Kisarazu
chosen
Kisarazu is a coastal city in Chiba Prefecture, Japan, known as the mainland terminus of the Tokyo Bay Aqua-Line expressway.
-
B.
Koshigaya
Koshigaya is a suburban city in Japan known for its large shopping complexes and residential communities within the Greater Tokyo metropolitan area.
-
C.
Higashikurume
Higashikurume is a suburban city in western Tokyo, Japan, known for its residential neighborhoods and role as a commuter area for central Tokyo.
-
D.
Kasukabe
Kasukabe is a city in Japan known for its suburban character within the Greater Tokyo area and as the setting of the popular manga and anime series "Crayon Shin-chan."
-
E.
Akiruno
Akiruno is a city in western Tokyo, Japan, known for its natural scenery, including rivers, forests, and hiking areas.
- 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_69c687f1a3048190828b7342f7125d5c |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6aff42c748190b818cf55f83647cb |
completed | March 27, 2026, 4:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1076c28b08190a5a0ab74ccfb9909 |
completed | April 4, 2026, 12:43 p.m. |
Created at: March 27, 2026, 2 p.m.