Triple

T8183375
Position Surface form Disambiguated ID Type / Status
Subject Minho region E191121 entity
Predicate hasMajorCity P316 FINISHED
Object Amares
Amares is a municipality in northern Portugal known for its rural landscapes, historical churches, and proximity to the city of Braga in the Minho region.
 E716729 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: Amares | Statement: [Minho region, hasMajorCity, Amares]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Amares
Context triple: [Minho region, hasMajorCity, Amares]
  • A. Amarar
    Amarar is the native name used by the Beja people to refer to themselves or their community.
  • B. Amreya
    Amreya is a district within Egypt’s Alexandria region, known for its mix of industrial zones, residential areas, and proximity to the Mediterranean coast.
  • C. Ameide
    Ameide is a small historic town in the Dutch province of South Holland, known for its location along the Lek River and traditional Dutch architecture.
  • D. Amuesha
    Amuesha is another name for the Yaneshaʼ language, an Arawakan language spoken by the Yaneshaʼ (Amuesha) people of central Peru.
  • E. Amed
    Amed is the historical name of the city now known as Diyarbakır, a major cultural and political center in southeastern Turkey, especially significant for Kurdish heritage.
  • 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: Amares
Triple: [Minho region, hasMajorCity, Amares]
Generated description
Amares is a municipality in northern Portugal known for its rural landscapes, historical churches, and proximity to the city of Braga in the Minho region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Amares
Target entity description: Amares is a municipality in northern Portugal known for its rural landscapes, historical churches, and proximity to the city of Braga in the Minho region.
  • A. Amarar
    Amarar is the native name used by the Beja people to refer to themselves or their community.
  • B. Amreya
    Amreya is a district within Egypt’s Alexandria region, known for its mix of industrial zones, residential areas, and proximity to the Mediterranean coast.
  • C. Ameide
    Ameide is a small historic town in the Dutch province of South Holland, known for its location along the Lek River and traditional Dutch architecture.
  • D. Amuesha
    Amuesha is another name for the Yaneshaʼ language, an Arawakan language spoken by the Yaneshaʼ (Amuesha) people of central Peru.
  • E. Amed
    Amed is a coastal fishing village and popular diving and snorkeling destination in eastern Bali, Indonesia, known for its black sand beaches and coral reefs.
  • 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_69ca82c4538081909404325aa5639483 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb4c4f4ef88190ad346edad14b67ee completed March 31, 2026, 4:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccbf8e8f0c819096f449760ce0d240 completed April 1, 2026, 6:47 a.m.
NEDg Description generation batch_69ccc315132c8190bb0ad49232ccc3b8 completed April 1, 2026, 7:02 a.m.
NED2 Entity disambiguation (via description) batch_69ccd87585148190a2d8b81ab352d123 completed April 1, 2026, 8:33 a.m.
Created at: March 30, 2026, 5:41 p.m.