Triple

T6869058
Position Surface form Disambiguated ID Type / Status
Subject Soraku District E158490 entity
Predicate formerSettlement P54403 FINISHED
Object Kamo
Kamo was a former town in Japan’s Kyoto Prefecture that was once part of Soraku District before being merged into a larger municipality.
 E625335 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: Kamo | Statement: [Soraku District, formerSettlement, Kamo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kamo
Context triple: [Soraku District, formerSettlement, Kamo]
  • A. Kamo
    Kamo is a residential suburb and community located just north of central Whangārei in New Zealand’s Northland Region.
  • B. Hamachō
    Hamachō is a neighborhood in Chūō ward, central Tokyo, known for its mix of residential areas, local businesses, and proximity to the Nihonbashi district.
  • C. Tenryu
    Tenryu is the original name of Japan's famed Blue Impulse aerobatic demonstration team.
  • D. Kawaiisu
    Kawaiisu is a Native American people and their Uto-Aztecan language traditionally spoken in the southern Sierra Nevada and Tehachapi Mountains of California.
  • E. Kamogawa
    Kamogawa is a prominent river running through Kyoto, Japan, known for its scenic banks, cultural significance, and popular walking paths.
  • 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: Kamo
Triple: [Soraku District, formerSettlement, Kamo]
Generated description
Kamo was a former town in Japan’s Kyoto Prefecture that was once part of Soraku District before being merged into a larger municipality.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kamo
Target entity description: Kamo was a former town in Japan’s Kyoto Prefecture that was once part of Soraku District before being merged into a larger municipality.
  • A. Kamo
    Kamo is a residential suburb and community located just north of central Whangārei in New Zealand’s Northland Region.
  • B. Hamachō
    Hamachō is a neighborhood in Chūō ward, central Tokyo, known for its mix of residential areas, local businesses, and proximity to the Nihonbashi district.
  • C. Tenryu
    Tenryu is the original name of Japan's famed Blue Impulse aerobatic demonstration team.
  • D. Kawaiisu
    Kawaiisu is a Native American people and their Uto-Aztecan language traditionally spoken in the southern Sierra Nevada and Tehachapi Mountains of California.
  • E. Kamogawa
    Kamogawa is a coastal city in Chiba Prefecture, Japan, known for its beaches, fishing industry, and the popular Kamogawa Sea World aquarium.
  • 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_69c68831e3648190a643c328122e4d43 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d8a916a88190b81551731dff2898 completed March 27, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c74299ae148190a56c7b1ee8829f40 completed March 28, 2026, 2:53 a.m.
NEDg Description generation batch_69c743a639f88190a0758194433322bf completed March 28, 2026, 2:57 a.m.
NED2 Entity disambiguation (via description) batch_69c7445fbd488190938ec3dd59cbeb2c completed March 28, 2026, 3 a.m.
Created at: March 27, 2026, 2:22 p.m.