Triple

T9765482
Position Surface form Disambiguated ID Type / Status
Subject Mobile Fleet E236977 entity
Predicate notableShip P3345 FINISHED
Object Mutsu
Mutsu was a Japanese Nagato-class battleship of the Imperial Japanese Navy that served prominently during the interwar period and World War II before being destroyed by an internal explosion in 1943.
 E877104 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: Mutsu | Statement: [Mobile Fleet, notableShip, Mutsu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mutsu
Context triple: [Mobile Fleet, notableShip, Mutsu]
  • A. Ōshū
    Ōshū is a city in Japan’s Tōhoku region known for its rural landscapes, historical sites, and agricultural production.
  • B. Seishirō
    Seishirō is a Japanese given name commonly used for male individuals.
  • C. Sumoto
    Sumoto is a coastal city located on Awaji Island in Japan, known for its hot springs, scenic views of the Seto Inland Sea, and citrus production.
  • D. Ichigaya
    Ichigaya is a central Tokyo district known for its major railway station, government and educational institutions, and proximity to the Imperial Palace area.
  • E. Ryōtsu
    Ryōtsu was a former city on Sado Island in Niigata Prefecture, Japan, known for its coastal setting and later incorporation into the city of Sado.
  • 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: Mutsu
Triple: [Mobile Fleet, notableShip, Mutsu]
Generated description
Mutsu was a Japanese Nagato-class battleship of the Imperial Japanese Navy that served prominently during the interwar period and World War II before being destroyed by an internal explosion in 1943.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mutsu
Target entity description: Mutsu was a Japanese Nagato-class battleship of the Imperial Japanese Navy that served prominently during the interwar period and World War II before being destroyed by an internal explosion in 1943.
  • A. Ōshū
    Ōshū is a city in Japan’s Tōhoku region known for its rural landscapes, historical sites, and agricultural production.
  • B. Seishirō
    Seishirō is a Japanese given name commonly used for male individuals.
  • C. Sumoto
    Sumoto is a coastal city located on Awaji Island in Japan, known for its hot springs, scenic views of the Seto Inland Sea, and citrus production.
  • D. Ichigaya
    Ichigaya is a central Tokyo district known for its major railway station, government and educational institutions, and proximity to the Imperial Palace area.
  • E. Ryōtsu
    Ryōtsu was a former city on Sado Island in Niigata Prefecture, Japan, known for its coastal setting and later incorporation into the city of Sado.
  • 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_69ca84d831b8819090322686b47887ce completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda0a040988190b1c940f9e5c42f9c completed April 1, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69d979c21f5481908bea7fd2c70d2c0b completed April 10, 2026, 10:29 p.m.
NEDg Description generation batch_69d97c7bc87481908d50eb6f294170eb completed April 10, 2026, 10:40 p.m.
NED2 Entity disambiguation (via description) batch_69d97e015b088190a97822675eecaa5a completed April 10, 2026, 10:47 p.m.
Created at: March 30, 2026, 8:25 p.m.