Triple
T3911316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beppu |
E87326
|
entity |
| Predicate | hasTransportation |
P105
|
FINISHED |
| Object |
Beppu Station
Beppu Station is the main railway hub serving the hot spring resort city of Beppu in Ōita Prefecture, Japan.
|
E849131
|
NE FINISHED |
How this triple was built (4 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: Beppu Station | Statement: [Beppu, hasTransportation, Beppu Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beppu Station Context triple: [Beppu, hasTransportation, Beppu Station]
-
A.
Sakurajima Station
Sakurajima Station is a railway station in Osaka, Japan, serving the JR Yumesaki Line near the Universal Studios Japan area.
-
B.
Ebisu Station
Ebisu Station is a major railway hub in Tokyo’s Shibuya ward, known for its convenient connections and proximity to the popular Ebisu commercial and entertainment district.
-
C.
Kitahama Station
Kitahama Station is a major underground railway station in Osaka, Japan, serving both the Osaka Metro and Keihan Electric Railway networks.
-
D.
Uguisudani Station
Uguisudani Station is a railway station in Tokyo, Japan, known for serving the Yamanote and Keihin-Tōhoku Lines near the Ueno area.
-
E.
Naha Station
Naha Station is a major railway terminal in Naha, Okinawa, serving as a key transportation hub for the city and surrounding region.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Beppu Station Triple: [Beppu, hasTransportation, Beppu Station]
Generated description
Beppu Station is the main railway hub serving the hot spring resort city of Beppu in Ōita Prefecture, Japan.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Beppu Station Target entity description: Beppu Station is the main railway hub serving the hot spring resort city of Beppu in Ōita Prefecture, Japan.
-
A.
Sakurajima Station
Sakurajima Station is a railway station in Osaka, Japan, serving the JR Yumesaki Line near the Universal Studios Japan area.
-
B.
Ebisu Station
Ebisu Station is a major railway hub in Tokyo’s Shibuya ward, known for its convenient connections and proximity to the popular Ebisu commercial and entertainment district.
-
C.
Kitahama Station
Kitahama Station is a major underground railway station in Osaka, Japan, serving both the Osaka Metro and Keihan Electric Railway networks.
-
D.
Uguisudani Station
Uguisudani Station is a railway station in Tokyo, Japan, known for serving the Yamanote and Keihin-Tōhoku Lines near the Ueno area.
-
E.
Naha Station
Naha Station is a major railway terminal in Naha, Okinawa, serving as a key transportation hub for the city and surrounding region.
- F. None of above. chosen
Provenance (5 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_69d5b790737c8190930dc863ffe95035 |
completed | April 8, 2026, 2:04 a.m. |
| NEDg | Description generation | batch_69d5bbfd698081909a9fccc16508917d |
completed | April 8, 2026, 2:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d5bcde232081909b2389d8b16e1733 |
completed | April 8, 2026, 2:26 a.m. |
Created at: March 9, 2026, 3:22 p.m.