Triple

T12652530
Position Surface form Disambiguated ID Type / Status
Subject 柏原市 E302198 entity
Predicate 河川 P165 FINISHED
Object 石川
石川は大阪府東部を流れ、大和川水系に属する中小河川です。
 E996588 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: 石川 | Statement: [柏原市, 河川, 石川]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 石川
Context triple: [柏原市, 河川, 石川]
  • A. 天野川
    天野川は大阪府交野市を流れる、七夕伝説や星にまつわるロマンチックな物語で知られる川です。
  • B. 玉川
    玉川 is a district in Tokyo’s Setagaya Ward known for its riverside location along the Tama River and its mix of residential areas and commercial facilities.
  • C. 桂川
    桂川は、京都市内を流れ嵐山の景観で知られる日本の代表的な河川の一つです。
  • D. Yamakita
    Yamakita is a rural town in Kanagawa Prefecture, Japan, known for its mountainous terrain, hot springs, and access to outdoor activities such as hiking and river sports.
  • E. Shimizu
    Shimizu is a prominent Japanese port city known for its busy harbor and scenic views of Mount Fuji.
  • 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: 石川
Triple: [柏原市, 河川, 石川]
Generated description
石川は大阪府東部を流れ、大和川水系に属する中小河川です。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 石川
Target entity description: 石川は大阪府東部を流れ、大和川水系に属する中小河川です。
  • A. 天野川
    天野川は大阪府交野市を流れる、七夕伝説や星にまつわるロマンチックな物語で知られる川です。
  • B. 玉川
    玉川 is a district in Tokyo’s Setagaya Ward known for its riverside location along the Tama River and its mix of residential areas and commercial facilities.
  • C. 桂川
    桂川は、京都市内を流れ嵐山の景観で知られる日本の代表的な河川の一つです。
  • D. Yamakita
    Yamakita is a rural town in Kanagawa Prefecture, Japan, known for its mountainous terrain, hot springs, and access to outdoor activities such as hiking and river sports.
  • E. Shimizu
    Shimizu is a prominent Japanese port city known for its busy harbor and scenic views of Mount Fuji.
  • 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_69d7bded71a88190bb76e2413af9ea66 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96160730c81909e1aa3efb51bf159 completed April 10, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6688104d48190939933b93b7e60cc completed May 2, 2026, 9:11 p.m.
NEDg Description generation batch_69f66c572f848190a8cad6311d3315a3 completed May 2, 2026, 9:27 p.m.
NED2 Entity disambiguation (via description) batch_69f66cef79148190a052fb9ade3b0d27 completed May 2, 2026, 9:30 p.m.
Created at: April 9, 2026, 5:18 p.m.