Triple

T6726240
Position Surface form Disambiguated ID Type / Status
Subject University of Granada E153524 entity
Predicate hasCampus P116 FINISHED
Object Armilla
Armilla is a municipality in the province of Granada, Spain, that hosts one of the campuses of the University of Granada.
 E614627 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: Armilla | Statement: [University of Granada, hasCampus, Armilla]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Armilla
Context triple: [University of Granada, hasCampus, Armilla]
  • A. Armills
    Armills are ceremonial arm bracelets traditionally worn by British monarchs during coronations as symbols of sincerity and wisdom.
  • B. Armamar
    Armamar is a Portuguese municipality in the Douro region, known for its terraced vineyards and wine production landscapes.
  • C. Armant
    Armant is a city in Egypt’s Luxor Governorate, known for its ancient Egyptian heritage and archaeological sites.
  • D. Brecheret
    Brecheret is the surname of Victor Brecheret, a prominent Italian-Brazilian modernist sculptor known for his monumental public works in Brazil.
  • E. Rogat
    Rogat is a small village in the Dutch province of Drenthe, known for its rural character and location within the municipality of De Wolden.
  • 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: Armilla
Triple: [University of Granada, hasCampus, Armilla]
Generated description
Armilla is a municipality in the province of Granada, Spain, that hosts one of the campuses of the University of Granada.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Armilla
Target entity description: Armilla is a municipality in the province of Granada, Spain, that hosts one of the campuses of the University of Granada.
  • A. Armills
    Armills are ceremonial arm bracelets traditionally worn by British monarchs during coronations as symbols of sincerity and wisdom.
  • B. Armamar
    Armamar is a Portuguese municipality in the Douro region, known for its terraced vineyards and wine production landscapes.
  • C. Armant
    Armant is a city in Egypt’s Luxor Governorate, known for its ancient Egyptian heritage and archaeological sites.
  • D. Brecheret
    Brecheret is the surname of Victor Brecheret, a prominent Italian-Brazilian modernist sculptor known for his monumental public works in Brazil.
  • E. Rogat
    Rogat is a small village in the Dutch province of Drenthe, known for its rural character and location within the municipality of De Wolden.
  • 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_69c6880afb988190ad88011b48ecfcba completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d15131f08190aba6c00943c51331 completed March 27, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c700a5428c81908d4484c3e3734076 completed March 27, 2026, 10:11 p.m.
NEDg Description generation batch_69c707ca6b188190af9b17171b7d912c completed March 27, 2026, 10:42 p.m.
NED2 Entity disambiguation (via description) batch_69c708869b6c81909da4677d72c4edcd completed March 27, 2026, 10:45 p.m.
Created at: March 27, 2026, 2:08 p.m.