Triple

T9048291
Position Surface form Disambiguated ID Type / Status
Subject 伊丹市 E216813 entity
Predicate borderWith P224 FINISHED
Object 兵庫県宝塚市
兵庫県宝塚市は、宝塚歌劇団や温泉で知られる、兵庫県南東部に位置する都市です。
 E774460 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: 兵庫県宝塚市 | Statement: [伊丹市, borderWith, 兵庫県宝塚市]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 兵庫県宝塚市
Context triple: [伊丹市, borderWith, 兵庫県宝塚市]
  • A. Habikino, Osaka
    Habikino is a city in Osaka Prefecture, Japan, historically notable for its large kofun burial mounds and ancient imperial tombs.
  • B. Naniwa-ku, Osaka
    Naniwa-ku, Osaka is a central ward of Osaka City known for its busy commercial districts, entertainment areas, and major transport hubs such as Namba.
  • C. Sakai, Osaka
    Sakai, Osaka is a historic port city in Japan’s Osaka Prefecture, known for its ancient burial mounds, traditional craftsmanship, and role as a major commercial center.
  • D. Konohana-ku, Osaka
    Konohana-ku, Osaka is a ward of Osaka City in Japan known for hosting major attractions like Universal Studios Japan and its themed entertainment areas.
  • E. Ikuno-ku, Osaka
    Ikuno-ku, Osaka is a residential ward in Osaka City known for its significant Korean community, dense urban neighborhoods, and convenient access to central Osaka via multiple rail and metro lines.
  • 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: 兵庫県宝塚市
Triple: [伊丹市, borderWith, 兵庫県宝塚市]
Generated description
兵庫県宝塚市は、宝塚歌劇団や温泉で知られる、兵庫県南東部に位置する都市です。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 兵庫県宝塚市
Target entity description: 兵庫県宝塚市は、宝塚歌劇団や温泉で知られる、兵庫県南東部に位置する都市です。
  • A. Habikino, Osaka
    Habikino is a city in Osaka Prefecture, Japan, historically notable for its large kofun burial mounds and ancient imperial tombs.
  • B. Naniwa-ku, Osaka
    Naniwa-ku, Osaka is a central ward of Osaka City known for its busy commercial districts, entertainment areas, and major transport hubs such as Namba.
  • C. Sakai, Osaka
    Sakai, Osaka is a historic port city in Japan’s Osaka Prefecture, known for its ancient burial mounds, traditional craftsmanship, and role as a major commercial center.
  • D. Konohana-ku, Osaka
    Konohana-ku, Osaka is a ward of Osaka City in Japan known for hosting major attractions like Universal Studios Japan and its themed entertainment areas.
  • E. Ikuno-ku, Osaka
    Ikuno-ku, Osaka is a residential ward in Osaka City known for its significant Korean community, dense urban neighborhoods, and convenient access to central Osaka via multiple rail and metro lines.
  • 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.