Triple

T11309734
Position Surface form Disambiguated ID Type / Status
Subject 八幡市 E267805 entity
Predicate 隣接自治体 P33892 FINISHED
Object 城陽市
城陽市は、京都府南部に位置し、住宅地と農地が広がる中規模の都市です。
 E917331 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: 城陽市 | Statement: [八幡市, 隣接自治体, 城陽市]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 城陽市
Context triple: [八幡市, 隣接自治体, 城陽市]
  • A. Shouguang
    Shouguang is a county-level city in Shandong Province, China, known as a major national hub for vegetable production and greenhouse agriculture.
  • B. Tengzhou City
    Tengzhou City is a county-level city in southern Shandong Province, China, known for its long history and role as an important regional industrial and transportation hub.
  • C. Qingzhou
    Qingzhou is a historic county-level city in eastern China known for its cultural heritage and location in central Shandong Province.
  • D. Linyi
    Linyi is a major prefecture-level city in southeastern Shandong Province, China, known for its large population, historical significance, and role as a regional commercial and logistics hub.
  • E. Zaozhuang City
    Zaozhuang City is a prefecture-level city in southern Shandong Province, China, known for its coal industry, historical sites, and the ancient canal town of Taierzhuang.
  • 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: 城陽市
Triple: [八幡市, 隣接自治体, 城陽市]
Generated description
城陽市は、京都府南部に位置し、住宅地と農地が広がる中規模の都市です。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 城陽市
Target entity description: 城陽市は、京都府南部に位置し、住宅地と農地が広がる中規模の都市です。
  • A. Shouguang
    Shouguang is a county-level city in Shandong Province, China, known as a major national hub for vegetable production and greenhouse agriculture.
  • B. Tengzhou City
    Tengzhou City is a county-level city in southern Shandong Province, China, known for its long history and role as an important regional industrial and transportation hub.
  • C. Qingzhou
    Qingzhou is a historic county-level city in eastern China known for its cultural heritage and location in central Shandong Province.
  • D. Linyi
    Linyi is a major prefecture-level city in southeastern Shandong Province, China, known for its large population, historical significance, and role as a regional commercial and logistics hub.
  • E. Zaozhuang City
    Zaozhuang City is a prefecture-level city in southern Shandong Province, China, known for its coal industry, historical sites, and the ancient canal town of Taierzhuang.
  • 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_69d6aaca5c24819083db46a30d86cb34 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9c0b3b88190ac0e3d6a5ad3b9bc completed April 9, 2026, 6:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69e50a70022081908bc74185003a3503 completed April 19, 2026, 5:01 p.m.
NEDg Description generation batch_69e510fb1e288190a7a38fe896d7b91d completed April 19, 2026, 5:29 p.m.
NED2 Entity disambiguation (via description) batch_69e516d0910481908fee176db0d9229b completed April 19, 2026, 5:54 p.m.
Created at: April 8, 2026, 9:32 p.m.