Triple

T11134266
Position Surface form Disambiguated ID Type / Status
Subject Sapporo Municipal Subway E263370 entity
Predicate hasStation P35 FINISHED
Object Asabu Station
Asabu Station is a subway station in Sapporo, Japan, serving as the northern terminus of the Sapporo Municipal Subway Namboku Line.
E1274230 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: Asabu Station | Statement: [Sapporo Municipal Subway, hasStation, Asabu Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Asabu Station
Context triple: [Sapporo Municipal Subway, hasStation, Asabu Station]
  • A. Asahibashi Station
    Asahibashi Station is a monorail station in Naha, Okinawa, serving as a key stop on the Okinawa Urban Monorail (Yui Rail) system.
  • B. Shinsugita Station
    Shinsugita Station is a railway station in Yokohama, Japan, serving as a local transit hub within the city's Isogo Ward.
  • C. Awaji Station
    Awaji Station is a railway station in Osaka, Japan, serving as an important junction for multiple Hankyu Railway lines.
  • D. Shibasaki Station
    Shibasaki Station is a railway station in Chōfu, Tokyo, serving local commuter traffic on one of the city’s private railway lines.
  • E. Uguisudani Station
    Uguisudani Station is a railway station in Tokyo, Japan, known for serving the Yamanote and Keihin-Tōhoku Lines near the Ueno area.
  • 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: Asabu Station
Triple: [Sapporo Municipal Subway, hasStation, Asabu Station]
Generated description
Asabu Station is a subway station in Sapporo, Japan, serving as the northern terminus of the Sapporo Municipal Subway Namboku Line.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Asabu Station
Target entity description: Asabu Station is a subway station in Sapporo, Japan, serving as the northern terminus of the Sapporo Municipal Subway Namboku Line.
  • A. Asahibashi Station
    Asahibashi Station is a monorail station in Naha, Okinawa, serving as a key stop on the Okinawa Urban Monorail (Yui Rail) system.
  • B. Shinsugita Station
    Shinsugita Station is a railway station in Yokohama, Japan, serving as a local transit hub within the city's Isogo Ward.
  • C. Awaji Station
    Awaji Station is a railway station in Osaka, Japan, serving as an important junction for multiple Hankyu Railway lines.
  • D. Shibasaki Station
    Shibasaki Station is a railway station in Chōfu, Tokyo, serving local commuter traffic on one of the city’s private railway lines.
  • E. Uguisudani Station
    Uguisudani Station is a railway station in Tokyo, Japan, known for serving the Yamanote and Keihin-Tōhoku Lines near the Ueno area.
  • 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_69d6aa9c0ba08190bbd19c217489b755 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8347a248190837e8c26f25f553a completed April 9, 2026, 5:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a01c9260c508190aa83d6bed8b598a6 completed May 11, 2026, 12:18 p.m.
NEDg Description generation batch_6a01cabea2b48190a690b17a88d45b40 completed May 11, 2026, 12:25 p.m.
NED2 Entity disambiguation (via description) batch_6a01cefa08f8819086cb86ce22193baa completed May 11, 2026, 12:43 p.m.
Created at: April 8, 2026, 9:28 p.m.