Triple

T11567043
Position Surface form Disambiguated ID Type / Status
Subject Atsugi E274278 entity
Predicate neighboringMunicipality P17964 FINISHED
Object Zama
Zama is a city in Kanagawa Prefecture, Japan, known for its residential character and proximity to major urban centers in the Greater Tokyo area.
 E933819 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: Zama | Statement: [Atsugi, neighboringMunicipality, Zama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zama
Context triple: [Atsugi, neighboringMunicipality, Zama]
  • A. Brida
    Brida is a novel by Brazilian author Paulo Coelho that follows a young Irish woman’s spiritual journey as she explores witchcraft, love, and self-discovery.
  • B. Achamán
    Achamán is the supreme creator god in the traditional religion of the Guanche people of Tenerife in the Canary Islands.
  • C. La Tzoumaz
    La Tzoumaz is a Swiss alpine village and ski resort in the 4 Vallées region, known for its family-friendly slopes and access to extensive interconnected ski terrain.
  • D. Yatta
    Yatta is a Palestinian city in the southern West Bank, located just south of Hebron and known for its agricultural character and historic roots.
  • E. La Fiera
    La Fiera is the popular nickname of Mexican football club Club León, reflecting its fierce and aggressive playing style.
  • 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: Zama
Triple: [Atsugi, neighboringMunicipality, Zama]
Generated description
Zama is a city in Kanagawa Prefecture, Japan, known for its residential character and proximity to major urban centers in the Greater Tokyo area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zama
Target entity description: Zama is a city in Kanagawa Prefecture, Japan, known for its residential character and proximity to major urban centers in the Greater Tokyo area.
  • A. Brida
    Brida is a novel by Brazilian author Paulo Coelho that follows a young Irish woman’s spiritual journey as she explores witchcraft, love, and self-discovery.
  • B. Achamán
    Achamán is the supreme creator god in the traditional religion of the Guanche people of Tenerife in the Canary Islands.
  • C. La Tzoumaz
    La Tzoumaz is a Swiss alpine village and ski resort in the 4 Vallées region, known for its family-friendly slopes and access to extensive interconnected ski terrain.
  • D. Yatta
    Yatta is a Palestinian city in the southern West Bank, located just south of Hebron and known for its agricultural character and historic roots.
  • E. La Fiera
    La Fiera is the popular nickname of Mexican football club Club León, reflecting its fierce and aggressive playing style.
  • 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_69d6aae5ac3c81908d2b0a3a665665b2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d88dd4305c8190ac5ff490b6b63e12 completed April 10, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69e6e8c9a22c8190812c64b9f305ae99 completed April 21, 2026, 3:02 a.m.
NEDg Description generation batch_69e6ef951eb881909810b5923385c4c6 completed April 21, 2026, 3:31 a.m.
NED2 Entity disambiguation (via description) batch_69e6f94ac2d0819098a3024eaab908b5 completed April 21, 2026, 4:12 a.m.
Created at: April 8, 2026, 9:37 p.m.