Triple
T17102373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tama area |
E415010
|
entity |
| Predicate | hasPart |
P35
|
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: [Tama area, hasPart, Hino]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hino Context triple: [Tama area, hasPart, 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.
Hino Motors Manufacturing Indonesia
Hino Motors Manufacturing Indonesia is an Indonesian commercial vehicle and components manufacturer that serves as Hino’s primary production base for trucks and buses in Southeast Asia.
-
E.
Toyo Bus
Toyo Bus is a regional bus company in Okinawa, Japan, providing public transportation services including routes operating from the Naha Bus Terminal.
- 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_69d886cfc8e88190b05ba466edd35591 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dc239a088190a776fe0f4361ffc7 |
completed | April 18, 2026, 7:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0139fdda488190a1ca5c7ca875e044 |
completed | May 11, 2026, 2:07 a.m. |
Created at: April 10, 2026, 5:35 a.m.