Triple

T9048306
Position Surface form Disambiguated ID Type / Status
Subject 伊丹市 E216813 entity
Predicate hasRiver P165 FINISHED
Object 天神川
天神川は兵庫県伊丹市を流れる中小河川で、市街地の治水や景観に寄与している川です。
 E774462 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: 天神川 | Statement: [伊丹市, hasRiver, 天神川]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 天神川
Context triple: [伊丹市, hasRiver, 天神川]
  • A. 庄川
    庄川は日本の中部地方を流れ、富山県の庄川峡などの景勝地や水力発電で知られる河川である。
  • B. 夙川
    夙川 is a scenic river area in Nishinomiya, Hyōgo Prefecture, Japan, renowned for its cherry blossom-lined banks and popular hanami spots.
  • 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. 富士川
    富士川は、山梨県と静岡県を流れ駿河湾に注ぐ、日本有数の急流として知られる大河川である。
  • E. 阿賀野川
    阿賀野川は福島県から新潟県へと流れ日本海に注ぐ、日本有数の流域面積と水力発電・灌漑機能を持つ大河川である。
  • 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: 天神川
Triple: [伊丹市, hasRiver, 天神川]
Generated description
天神川は兵庫県伊丹市を流れる中小河川で、市街地の治水や景観に寄与している川です。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 天神川
Target entity description: 天神川は兵庫県伊丹市を流れる中小河川で、市街地の治水や景観に寄与している川です。
  • A. 庄川
    庄川は日本の中部地方を流れ、富山県の庄川峡などの景勝地や水力発電で知られる河川である。
  • B. 夙川
    夙川 is a scenic river area in Nishinomiya, Hyōgo Prefecture, Japan, renowned for its cherry blossom-lined banks and popular hanami spots.
  • 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. 富士川
    富士川は、山梨県と静岡県を流れ駿河湾に注ぐ、日本有数の急流として知られる大河川である。
  • E. 阿賀野川
    阿賀野川は福島県から新潟県へと流れ日本海に注ぐ、日本有数の流域面積と水力発電・灌漑機能を持つ大河川である。
  • 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_69ca83d362e88190ae44b4e4dc194209 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc6b51aa708190a37feecfd8deed2f completed April 1, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfebc0fd648190b0dd6cf62605b98f completed April 3, 2026, 4:33 p.m.
NEDg Description generation batch_69cfed4fb6cc8190bb97345dd392b25b completed April 3, 2026, 4:39 p.m.
NED2 Entity disambiguation (via description) batch_69cfedf299908190852cc627fd7134b9 completed April 3, 2026, 4:42 p.m.
Created at: March 30, 2026, 7:09 p.m.