Triple
T22761103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hanazono Kintetsu Liners |
E562989
|
entity |
| Predicate | formerName |
P65
|
FINISHED |
| Object | Kintetsu Liners |
—
|
NE NERFINISHED |
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: Kintetsu Liners | Statement: [Hanazono Kintetsu Liners, formerName, Kintetsu Liners]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kintetsu Liners Context triple: [Hanazono Kintetsu Liners, formerName, Kintetsu Liners]
-
A.
Kintetsu Liners
chosen
Kintetsu Liners is a Japanese professional rugby union team based in Higashi-Osaka, competing in Japan Rugby League One.
-
B.
Kintetsu Railway
Kintetsu Railway is a major Japanese private railway operator in the Kansai region, known for its extensive interurban network connecting cities such as Osaka, Nara, Kyoto, and Nagoya.
-
C.
Hankyu Railway
Hankyu Railway is a major private railway operator in the Kansai region of Japan, known for its extensive commuter network linking Osaka with Kyoto and Kobe.
-
D.
Kintetsu Bus
Kintetsu Bus is a Japanese bus company providing local and long-distance passenger transportation services as part of the Kintetsu Group.
-
E.
Kinki Sharyo
Kinki Sharyo is a Japanese manufacturer specializing in the design and production of railway vehicles, including metro and light rail trains used in systems worldwide.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24552e11c81909c2d61578a558bd7 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17a7c45b881908b29ba1439038789 |
completed | April 29, 2026, 3:26 a.m. |
Created at: April 17, 2026, 3:26 p.m.