Triple
T7854858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese carrier Zuiho |
E182147
|
entity |
| Predicate | previousName |
P65
|
FINISHED |
| Object | Takasaki |
E513533
|
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: Takasaki | Statement: [Japanese carrier Zuiho, previousName, Takasaki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Takasaki Context triple: [Japanese carrier Zuiho, previousName, Takasaki]
-
A.
Takasaki
chosen
Takasaki is a city in Japan’s Gunma Prefecture known for its Daruma doll production and as a regional commercial and transportation hub.
-
B.
Akishima
Akishima is a city in western Tokyo, Japan, known as part of the Tama area and characterized by its residential neighborhoods and light industry.
-
C.
Maebashi
Maebashi is the capital city of Gunma Prefecture in Japan, known as a regional administrative and commercial center on the Kantō Plain.
-
D.
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.
-
E.
Yokkaichi
Yokkaichi is an industrial port city in central Japan known for its petrochemical complexes and role as a major manufacturing hub.
- 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_69ca82869ee08190b8f9040dbc2c0467 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb1a72cfdc8190a3186c4c2894f571 |
completed | March 31, 2026, 12:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f1658e03a8819098ea2ac2f818a61a |
completed | April 29, 2026, 1:57 a.m. |
Created at: March 30, 2026, 4:51 p.m.