Triple

T5686146
Position Surface form Disambiguated ID Type / Status
Subject Rokkomichi Station E125317 entity
Predicate serves P98 FINISHED
Object Nada-ku
Nada-ku is a ward of Kobe in Japan’s Hyōgo Prefecture, known for its sake breweries, residential neighborhoods, and proximity to Mount Rokko.
 E541472 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: Nada-ku | Statement: [Rokkomichi Station, serves, Nada-ku]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nada-ku
Context triple: [Rokkomichi Station, serves, Nada-ku]
  • A. Naka-ku
    Naka-ku is a central ward of Yokohama, Japan, known for its historic port area, Chinatown, and major commercial and entertainment districts.
  • B. Nakawa
    Nakawa is one of the energetic human hosts in Disney’s “Festival of the Lion King” stage show at Disney’s Animal Kingdom.
  • C. Minamitane
    Minamitane is a town on Tanegashima Island in Kagoshima Prefecture, Japan, known for hosting Japan’s main spaceport facilities nearby.
  • D. Nakanai
    Nakanai is an Austronesian language spoken on the island of New Britain in Papua New Guinea, known for its role in the linguistic diversity of the Bismarck Archipelago.
  • E. Oimachi
    Oimachi is a commercial and residential district in Tokyo known for its busy train hub, shopping streets, and convenient access to central Shinagawa and other parts of the city.
  • 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: Nada-ku
Triple: [Rokkomichi Station, serves, Nada-ku]
Generated description
Nada-ku is a ward of Kobe in Japan’s Hyōgo Prefecture, known for its sake breweries, residential neighborhoods, and proximity to Mount Rokko.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nada-ku
Target entity description: Nada-ku is a ward of Kobe in Japan’s Hyōgo Prefecture, known for its sake breweries, residential neighborhoods, and proximity to Mount Rokko.
  • A. Naka-ku
    Naka-ku is a central ward of Yokohama, Japan, known for its historic port area, Chinatown, and major commercial and entertainment districts.
  • B. Nakawa
    Nakawa is one of the energetic human hosts in Disney’s “Festival of the Lion King” stage show at Disney’s Animal Kingdom.
  • C. Minamitane
    Minamitane is a town on Tanegashima Island in Kagoshima Prefecture, Japan, known for hosting Japan’s main spaceport facilities nearby.
  • D. Nakanai
    Nakanai is an Austronesian language spoken on the island of New Britain in Papua New Guinea, known for its role in the linguistic diversity of the Bismarck Archipelago.
  • E. Oimachi
    Oimachi is a commercial and residential district in Tokyo known for its busy train hub, shopping streets, and convenient access to central Shinagawa and other parts of the city.
  • 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_69c0082a884c8190a79001bae658941f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c023bbfb988190bb61c7d183660d5d completed March 22, 2026, 5:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a40b3808190bc57fde5990ac04e completed March 22, 2026, 9:08 p.m.
NEDg Description generation batch_69c05cd2dea88190bc79ca0a7709e7ca completed March 22, 2026, 9:19 p.m.
NED2 Entity disambiguation (via description) batch_69c05d8c85f88190a1a962794eeecd8d completed March 22, 2026, 9:22 p.m.
Created at: March 22, 2026, 3:44 p.m.