Triple

T14168565
Position Surface form Disambiguated ID Type / Status
Subject 伊藤 清 E351143 entity
Predicate 出身地 P1 FINISHED
Object 千葉県
千葉県は、日本の関東地方に位置し、成田国際空港や東京湾アクアライン、房総半島の海岸などで知られる県です。
E1168962 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: 千葉県 | Statement: [伊藤 清, 出身地, 千葉県]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 千葉県
Context triple: [伊藤 清, 出身地, 千葉県]
  • A. Ibaraki Prefecture
    Ibaraki Prefecture is a region in eastern Japan known for its agriculture, coastal landscapes, and scientific research centers such as the city of Tsukuba.
  • B. Ibaraki
    Ibaraki is a city in northern Osaka Prefecture, Japan, known as a residential and industrial hub within the Kansai metropolitan area.
  • C. Kanagawa Prefecture
    Kanagawa Prefecture is a coastal region in Japan’s Kantō area, known for its major port city of Yokohama, historic Kamakura, and proximity to Tokyo.
  • D. Saitama Prefecture
    Saitama Prefecture is a landlocked administrative region in the Kantō area of Japan, just north of Tokyo, known for its large commuter population, industrial centers, and cultural sites.
  • E. Miyagi Prefecture
    Miyagi Prefecture is a coastal region in Japan’s Tōhoku area, known for its capital city Sendai, scenic Matsushima Bay, and a mix of urban centers and rich natural landscapes.
  • 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: 千葉県
Triple: [伊藤 清, 出身地, 千葉県]
Generated description
千葉県は、日本の関東地方に位置し、成田国際空港や東京湾アクアライン、房総半島の海岸などで知られる県です。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 千葉県
Target entity description: 千葉県は、日本の関東地方に位置し、成田国際空港や東京湾アクアライン、房総半島の海岸などで知られる県です。
  • A. Ibaraki Prefecture
    Ibaraki Prefecture is a region in eastern Japan known for its agriculture, coastal landscapes, and scientific research centers such as the city of Tsukuba.
  • B. Ibaraki
    Ibaraki is a city in northern Osaka Prefecture, Japan, known as a residential and industrial hub within the Kansai metropolitan area.
  • C. Kanagawa Prefecture
    Kanagawa Prefecture is a coastal region in Japan’s Kantō area, known for its major port city of Yokohama, historic Kamakura, and proximity to Tokyo.
  • D. Saitama Prefecture
    Saitama Prefecture is a landlocked administrative region in the Kantō area of Japan, just north of Tokyo, known for its large commuter population, industrial centers, and cultural sites.
  • E. Miyagi Prefecture
    Miyagi Prefecture is a coastal region in Japan’s Tōhoku area, known for its capital city Sendai, scenic Matsushima Bay, and a mix of urban centers and rich natural landscapes.
  • 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_69d8278775fc8190b0802d22ca2f495d completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61b355f08190864c7322bbcb766d completed April 14, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff677935408190a28af4cd34d82aa4 completed May 9, 2026, 4:57 p.m.
NEDg Description generation batch_69ff67f64d2c81908fd2d8a09cd0b369 completed May 9, 2026, 4:59 p.m.
NED2 Entity disambiguation (via description) batch_69ff6888a85481909e8cdd34ed230fa4 completed May 9, 2026, 5:02 p.m.
Created at: April 10, 2026, 1 a.m.