Triple

T6826095
Position Surface form Disambiguated ID Type / Status
Subject La Orotava E157018 entity
Predicate borders P224 FINISHED
Object Santa Úrsula
Santa Úrsula is a coastal municipality on the northern side of Tenerife in Spain’s Canary Islands, known for its steep Atlantic cliffs, vineyards, and residential tourism.
 E621619 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: Santa Úrsula | Statement: [La Orotava, borders, Santa Úrsula]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Santa Úrsula
Context triple: [La Orotava, borders, Santa Úrsula]
  • A. Santa Úrsula
    Santa Úrsula is a neighborhood in Mexico City best known for hosting the iconic Estadio Azteca football stadium.
  • B. Saint Isabel
    Saint Isabel is a Christian saint traditionally associated with charity, humility, and service to the poor, venerated in various regions that bear her name.
  • C. Saint Ursula
    Saint Ursula is a legendary Christian virgin martyr, venerated especially in medieval Europe as the leader of a group of virgins martyred at Cologne.
  • D. Clementina
    Clementina is a feminine given name, often considered a variant of Clementine, used in various European and Latin American cultures.
  • E. Christiana
    Christiana is a personal name used as a given name, notably borne by individuals such as Christiana Wyly.
  • 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: Santa Úrsula
Triple: [La Orotava, borders, Santa Úrsula]
Generated description
Santa Úrsula is a coastal municipality on the northern side of Tenerife in Spain’s Canary Islands, known for its steep Atlantic cliffs, vineyards, and residential tourism.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Santa Úrsula
Target entity description: Santa Úrsula is a coastal municipality on the northern side of Tenerife in Spain’s Canary Islands, known for its steep Atlantic cliffs, vineyards, and residential tourism.
  • A. Santa Úrsula
    Santa Úrsula is a neighborhood in Mexico City best known for hosting the iconic Estadio Azteca football stadium.
  • B. Saint Isabel
    Saint Isabel is a Christian saint traditionally associated with charity, humility, and service to the poor, venerated in various regions that bear her name.
  • C. Saint Ursula
    Saint Ursula is a legendary Christian virgin martyr, venerated especially in medieval Europe as the leader of a group of virgins martyred at Cologne.
  • D. Clementina
    Clementina is a feminine given name, often considered a variant of Clementine, used in various European and Latin American cultures.
  • E. Christiana
    Christiana is a personal name used as a given name, notably borne by individuals such as Christiana Wyly.
  • 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_69c6882a5b5c8190917a7db9ed36bad1 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d58375248190935dd38d618994e3 completed March 27, 2026, 7:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c723f12a148190adbb05782a2041b6 completed March 28, 2026, 12:42 a.m.
NEDg Description generation batch_69c7251ec97c819094fb2a73ac1d1d0e completed March 28, 2026, 12:47 a.m.
NED2 Entity disambiguation (via description) batch_69c725d04d988190a4a6a1c73056cfd7 completed March 28, 2026, 12:50 a.m.
Created at: March 27, 2026, 2:18 p.m.