Triple
T8739480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | heavy cruiser Maya |
E207464
|
entity |
| Predicate | sisterShip |
P3142
|
FINISHED |
| Object | Takao |
E616898
|
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: Takao | Statement: [heavy cruiser Maya, sisterShip, Takao]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Takao Context triple: [heavy cruiser Maya, sisterShip, Takao]
-
A.
Takao
chosen
Takao was a lead Takao-class heavy cruiser of the Imperial Japanese Navy that served prominently in the Pacific Theater during World War II.
-
B.
Ōyama
Ōyama is a Japanese surname borne by various notable figures in Japan’s military, political, and cultural history.
-
C.
Yamashina
Yamashina is a Japanese noble family name historically associated with a cadet branch of the Imperial Family.
-
D.
Fukuchiyama
Fukuchiyama is a regional city in northern Kyoto Prefecture, Japan, known as a historical castle town and commercial hub for the surrounding rural area.
-
E.
Yashio
Yashio is a city in Saitama Prefecture, Japan, located on the outskirts of Tokyo and functioning largely as a residential commuter town.
- 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_69ca835a03a081909d4d4cd01a18c9fb |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d486e34819094a6c6ec26c047cf |
completed | March 31, 2026, 11:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d121cb33188190b5b70020a041c18f |
completed | April 4, 2026, 2:35 p.m. |
Created at: March 30, 2026, 6:38 p.m.