Triple

T30785831
Position Surface form Disambiguated ID Type / Status
Subject 広島市現代美術館 E783951 entity
Predicate 最寄交通機関 P3791 FINISHED
Object 広島電鉄皆実線
広島電鉄皆実線は、広島市中心部と南区皆実町方面を結び、沿線の商業施設や文化施設へのアクセスを担う広島電鉄の路面電車路線です。
E1930338 NE FINISHED

How this triple was built (3 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: 広島電鉄皆実線 | Statement: [広島市現代美術館, 最寄交通機関, 広島電鉄皆実線]
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: 広島電鉄皆実線
Triple: [広島市現代美術館, 最寄交通機関, 広島電鉄皆実線]
Generated description
広島電鉄皆実線は、広島市中心部と南区皆実町方面を結び、沿線の商業施設や文化施設へのアクセスを担う広島電鉄の路面電車路線です。
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: 最寄交通機関
Context triple: [広島市現代美術館, 最寄交通機関, 広島電鉄皆実線]
  • A. 最寄り在来線駅
    Indicates the relationship where a given location is associated with its nearest conventional (non-high-speed) railway station.
  • B. nearestShinkansenStation
    Indicates that one entity is the Shinkansen (bullet train) station geographically closest to the other entity.
  • C. nearestMajorTransportHub
    Indicates that one location is the closest significant transportation center (such as a major train station, airport, or bus terminal) to another location.
  • D. formerTerminalStation
    Indicates that a location once served as the end point (terminus) of a transportation line or route but no longer holds that status.
  • E. hasPublicTransportConnection chosen
    Indicates that there is an available public transportation link or service connecting the related entities.
  • F. None of above.

Provenance (6 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_69f224b213c8819083886073f90b647e completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f68fe8168c8190b083be0e33988b9c completed May 2, 2026, 11:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28b0a7a9988190892052e9d99f13a9 completed June 10, 2026, 12:32 a.m.
NEDg Description generation batch_6a28b1ecd9448190a88b0f465f97a8ba completed June 10, 2026, 12:38 a.m.
NED2 Entity disambiguation (via description) batch_6a28b28f98288190af9d9c0ea08b4254 completed June 10, 2026, 12:40 a.m.
PD Predicate disambiguation batch_69f686140aa08190a35f62572b2db9b6 completed May 2, 2026, 11:17 p.m.
Created at: April 29, 2026, 8:41 p.m.