Triple

T11309735
Position Surface form Disambiguated ID Type / Status
Subject 八幡市 E267805 entity
Predicate 隣接自治体 P33892 FINISHED
Object 京田辺市
京田辺市は、京都府南部に位置し、同志社大学のキャンパスなどを擁する住宅都市・学園都市として知られる市です。
E918727 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: 京田辺市 | Statement: [八幡市, 隣接自治体, 京田辺市]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 京田辺市
Context triple: [八幡市, 隣接自治体, 京田辺市]
  • A. Fujiyoshida-shi
    Fujiyoshida-shi is a city in Yamanashi Prefecture, Japan, located at the northern base of Mount Fuji and known as a gateway to the mountain.
  • B. Katsuragi-shi
    Katsuragi-shi is a city located in Nara Prefecture in Japan, known for its historical sites and proximity to the Katsuragi mountain range.
  • C. Azumino City
    Azumino City is a scenic municipality in central Japan known for its rural landscapes, clear spring water, and views of the Northern Japan Alps.
  • D. Takehara-shi
    Takehara-shi is a coastal city in Hiroshima Prefecture, Japan, known for its well-preserved historic townscape and traditional salt-making heritage.
  • E. Iwanuma City
    Iwanuma City is a coastal municipality in northeastern Japan known for its agricultural landscape and proximity to Sendai in Miyagi Prefecture.
  • 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: 京田辺市
Triple: [八幡市, 隣接自治体, 京田辺市]
Generated description
京田辺市は、京都府南部に位置し、同志社大学のキャンパスなどを擁する住宅都市・学園都市として知られる市です。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 京田辺市
Target entity description: 京田辺市は、京都府南部に位置し、同志社大学のキャンパスなどを擁する住宅都市・学園都市として知られる市です。
  • A. Fujiyoshida-shi
    Fujiyoshida-shi is a city in Yamanashi Prefecture, Japan, located at the northern base of Mount Fuji and known as a gateway to the mountain.
  • B. Katsuragi-shi
    Katsuragi-shi is a city located in Nara Prefecture in Japan, known for its historical sites and proximity to the Katsuragi mountain range.
  • C. Azumino City
    Azumino City is a scenic municipality in central Japan known for its rural landscapes, clear spring water, and views of the Northern Japan Alps.
  • D. Takehara-shi
    Takehara-shi is a coastal city in Hiroshima Prefecture, Japan, known for its well-preserved historic townscape and traditional salt-making heritage.
  • E. Iwanuma City
    Iwanuma City is a coastal municipality in northeastern Japan known for its agricultural landscape and proximity to Sendai in Miyagi Prefecture.
  • 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_69e525b4bdb88190b22d64eb65e97d9d completed April 19, 2026, 6:57 p.m.
NEDg Description generation batch_69e52c81449c8190847b64fa91a45b2e completed April 19, 2026, 7:26 p.m.
NED2 Entity disambiguation (via description) batch_69e5319b6ef0819096debabfb6ffbe70 completed April 19, 2026, 7:48 p.m.
Created at: April 8, 2026, 9:32 p.m.