Triple

T6802691
Position Surface form Disambiguated ID Type / Status
Subject Sasang Intercity Bus Terminal E156222 entity
Predicate connectsTo P845 FINISHED
Object Masan E581969 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: Masan | Statement: [Sasang Intercity Bus Terminal, connectsTo, Masan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Masan
Context triple: [Sasang Intercity Bus Terminal, connectsTo, Masan]
  • A. Masan chosen
    Masan is a city in South Korea that serves as a regional administrative and judicial center, hosting a seat of the country's district courts.
  • B. Nago
    Nago is a coastal city in northern Okinawa, Japan, known for its beaches, subtropical climate, and role as a regional commercial and cultural center.
  • C. Toyokawa
    Toyokawa is a city in Aichi Prefecture, Japan, known for its historic Toyokawa Inari temple and manufacturing industries.
  • D. Namba City
    Namba City is a large shopping and entertainment complex in Osaka’s Namba district, featuring retail stores, restaurants, offices, and a rooftop garden integrated with the surrounding urban landscape.
  • E. Sendai
    Sendai is the largest city in Japan’s Tōhoku region, known for its lush greenery, historic sites, and status as a major economic and cultural center in northeastern Honshu.
  • 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_69c68826e6a48190a3d220b541e639de completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d2e714d4819084c8109c4de7de72 completed March 27, 2026, 6:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c71a9b0cc48190819380aeaf0228e7 completed March 28, 2026, 12:02 a.m.
Created at: March 27, 2026, 2:16 p.m.