Triple
T10242695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tabata Station |
E243634
|
entity |
| Predicate | servesArea |
P82
|
FINISHED |
| Object |
Tabata district
Tabata district is a neighborhood in Tokyo, Japan, known as a residential area with convenient rail access via Tabata Station.
|
E852993
|
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: Tabata district | Statement: [Tabata Station, servesArea, Tabata district]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tabata district Context triple: [Tabata Station, servesArea, Tabata district]
-
A.
Hachiken district
Hachiken district is a neighborhood within Nishi-ku, Sapporo, known as a primarily residential area with local shops and community facilities.
-
B.
Tenma district
Tenma district is a bustling urban neighborhood in Osaka, Japan, known for its traditional shopping arcades, lively nightlife, and historic Tenmangu Shrine.
-
C.
Tsuzuki District
Tsuzuki District is a former administrative district that once existed within Kyoto Prefecture in Japan.
-
D.
Tsuboya district
Tsuboya district is a historic area in Naha, Okinawa, renowned as the traditional center of Ryukyuan pottery production and culture.
-
E.
Tempozan district
Tempozan district is a waterfront area in Osaka, Japan, known for attractions such as the Tempozan Ferris Wheel and Osaka Aquarium Kaiyukan.
- 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: Tabata district Triple: [Tabata Station, servesArea, Tabata district]
Generated description
Tabata district is a neighborhood in Tokyo, Japan, known as a residential area with convenient rail access via Tabata Station.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tabata district Target entity description: Tabata district is a neighborhood in Tokyo, Japan, known as a residential area with convenient rail access via Tabata Station.
-
A.
Hachiken district
Hachiken district is a neighborhood within Nishi-ku, Sapporo, known as a primarily residential area with local shops and community facilities.
-
B.
Tenma district
Tenma district is a bustling urban neighborhood in Osaka, Japan, known for its traditional shopping arcades, lively nightlife, and historic Tenmangu Shrine.
-
C.
Tsuzuki District
Tsuzuki District is a former administrative district that once existed within Kyoto Prefecture in Japan.
-
D.
Tsuboya district
Tsuboya district is a historic area in Naha, Okinawa, renowned as the traditional center of Ryukyuan pottery production and culture.
-
E.
Tempozan district
Tempozan district is a waterfront area in Osaka, Japan, known for attractions such as the Tempozan Ferris Wheel and Osaka Aquarium Kaiyukan.
- 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_69d381b0f97c819085c9b45799a5fb7c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d229c1ac8190a86e911aea47a56d |
completed | April 7, 2026, 9:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f78a6efc819091f8303a6cfe4c8b |
completed | April 9, 2026, 12:49 a.m. |
| NEDg | Description generation | batch_69d6fcaa16788190a4c7ef79a78febc6 |
completed | April 9, 2026, 1:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d6fd6d705c81908e469068937a79b3 |
completed | April 9, 2026, 1:14 a.m. |
Created at: April 6, 2026, 11:25 a.m.