Triple
T3911236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hino Motors, Ltd. |
E87325
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object | Hino |
E193096
|
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: Hino | Statement: [Hino Motors, Ltd., brand, Hino]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hino Context triple: [Hino Motors, Ltd., brand, Hino]
-
A.
Hino
Hino is a town in Shiga Prefecture, Japan, known for its historical streetscapes and traditional industries.
-
B.
Hino
chosen
Hino is a city in western Tokyo, Japan, known as a residential and industrial suburb within the Tama area.
-
C.
Hino Motors, Ltd.
Hino Motors, Ltd. is a Japanese manufacturer specializing in commercial vehicles and diesel engines, known particularly for its trucks and buses.
-
D.
Isuzu
Isuzu is a Japanese automotive manufacturer best known for producing commercial vehicles, pickup trucks, and diesel engines for global markets.
-
E.
Isuzu Elf
The Isuzu Elf is a line of light-duty commercial trucks produced by Japanese manufacturer Isuzu, widely used for urban delivery and utility applications.
- 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_69aed9424514819086e9c58adde6652d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeed35e2d081908b5d87c7630e7ffc |
completed | March 9, 2026, 3:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b51cb454c48190bf47d080f6cc24f0 |
completed | March 14, 2026, 8:30 a.m. |
Created at: March 9, 2026, 3:22 p.m.