Triple
T12594520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Center Force |
E300699
|
entity |
| Predicate | ship |
P880
|
FINISHED |
| Object | Chikuma |
E881729
|
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: Chikuma | Statement: [Center Force, ship, Chikuma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chikuma Context triple: [Center Force, ship, Chikuma]
-
A.
Chikuma
chosen
Chikuma was a Japanese Imperial Navy heavy cruiser that served prominently in World War II, including major Pacific naval battles.
-
B.
Chikugo
Chikugo is a city in southwestern Japan known for its agricultural production and traditional crafts within Fukuoka Prefecture on Kyushu Island.
-
C.
Takinogawa
Takinogawa is a residential district in Kita Ward, Tokyo, known for its quiet neighborhoods and convenient urban access.
-
D.
Kizugawa
Kizugawa is a city in southern Kyoto Prefecture, Japan, known for its mix of historical sites, residential areas, and growing industrial and research facilities.
-
E.
Kisogawa
Kisogawa is the Japanese name for the Kiso River, a major river in central Honshu known for its scenic valleys and historical importance.
- 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_69d7bdea2ca881908f379526c13b1145 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954cde3c0819094e74413d6dcf548 |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe729766008190803c1dfef2c8c872 |
completed | May 8, 2026, 11:32 p.m. |
Created at: April 9, 2026, 5:08 p.m.