Triple

T10619523
Position Surface form Disambiguated ID Type / Status
Subject Hannut E295670 entity
Predicate hasSubdivision P747 FINISHED
Object Wansin
Wansin is a village in the municipality of Hannut in the province of Liège, Belgium.
E877037 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: Wansin | Statement: [Hannut, hasSubdivision, Wansin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wansin
Context triple: [Hannut, hasSubdivision, Wansin]
  • A. Wako
    Wako is a suburban city in Saitama Prefecture, Japan, located on the northern outskirts of Tokyo and known as a residential and commuter hub.
  • B. Tenjin
    Tenjin is the Shinto kami of scholarship and learning, widely revered by students seeking academic success.
  • C. Yakumo
    Yakumo is a residential neighborhood in Tokyo’s Meguro ward known for its quiet streets, schools, and proximity to parks and shopping areas.
  • D. Togoshi
    Togoshi is a residential and commercial neighborhood in Tokyo’s Shinagawa ward, known for its traditional shopping streets and local atmosphere.
  • E. Narusawa
    Narusawa is a village in Yamanashi Prefecture, Japan, located in the scenic Fuji Five Lakes region near 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: Wansin
Triple: [Hannut, hasSubdivision, Wansin]
Generated description
Wansin is a village in the municipality of Hannut in the province of Liège, Belgium.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Wansin
Target entity description: Wansin is a village in the municipality of Hannut in the province of Liège, Belgium.
  • A. Wako
    Wako is a suburban city in Saitama Prefecture, Japan, located on the northern outskirts of Tokyo and known as a residential and commuter hub.
  • B. Tenjin
    Tenjin is the Shinto kami of scholarship and learning, widely revered by students seeking academic success.
  • C. Yakumo
    Yakumo is a residential neighborhood in Tokyo’s Meguro ward known for its quiet streets, schools, and proximity to parks and shopping areas.
  • D. Togoshi
    Togoshi is a residential and commercial neighborhood in Tokyo’s Shinagawa ward, known for its traditional shopping streets and local atmosphere.
  • E. Narusawa
    Narusawa is a village in Yamanashi Prefecture, Japan, located in the scenic Fuji Five Lakes region near 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_69d6ad9e653c8190b1473c860ee53dae completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d6df6fc47c8190b77b61a7fd223d65 completed April 8, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69d97a2c8a048190b9a62f1c68ac217a completed April 10, 2026, 10:31 p.m.
NEDg Description generation batch_69d97cc07100819088683a0d79b2baa0 completed April 10, 2026, 10:42 p.m.
NED2 Entity disambiguation (via description) batch_69d97e015b088190a97822675eecaa5a completed April 10, 2026, 10:47 p.m.
Created at: April 8, 2026, 8:21 p.m.