Triple
T16592547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Namboku Line |
E403125
|
entity |
| Predicate | passesThroughWard |
P45427
|
FINISHED |
| Object | Minato |
—
|
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: Minato | Statement: [Namboku Line, passesThroughWard, Minato]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Minato Context triple: [Namboku Line, passesThroughWard, Minato]
-
A.
Minato
chosen
Minato is a central special ward of Tokyo known for its major business districts, foreign embassies, and landmarks such as Tokyo Tower and Roppongi.
-
B.
Minato-ku
Minato-ku is a central ward of Osaka, Japan, known for its waterfront attractions and major landmarks such as the Osaka Aquarium Kaiyukan.
-
C.
Kōtō
Kōtō is a special ward in eastern Tokyo, Japan, known for its mix of residential neighborhoods, waterfront areas, and commercial districts.
-
D.
Minato Mirai district
Minato Mirai district is a modern waterfront urban area in Yokohama, Japan, known for its high-rise skyline, shopping and entertainment complexes, and scenic harbor views.
-
E.
Minato City (Minato-ku)
Minato City (Minato-ku) is a central Tokyo ward known for its major business districts, embassies, and landmarks such as Roppongi, Odaiba, and Tokyo Tower.
- 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_69d88387363c8190a97a0c942130de97 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e359a123e8819095cd73cd848a3345 |
completed | April 18, 2026, 10:14 a.m. |
Created at: April 10, 2026, 5:16 a.m.