Triple

T887731
Position Surface form Disambiguated ID Type / Status
Subject Marian apparitions at Fatima E19167 entity
Predicate hasLocation P40 FINISHED
Object Fátima
Fátima is a town in central Portugal renowned as a major Catholic pilgrimage site associated with reported Marian apparitions in 1917.
 E105859 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: Fátima | Statement: [Marian apparitions at Fatima, hasLocation, Fátima]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Fátima
Context triple: [Marian apparitions at Fatima, hasLocation, Fátima]
  • A. María
    María is a key character in Ernest Hemingway's novel "For Whom the Bell Tolls," known as a young Spanish woman and love interest of the protagonist amid the Spanish Civil War.
  • B. Francisca
    Francisca is a feminine given name, used in various European and Latin American cultures, that is cognate with the English name Frances.
  • C. Belén
    Belén is a town in northwestern Argentina known for its traditional weaving and role as a regional center in Catamarca Province.
  • D. Teresa
    Teresa is the religious name of Mother Teresa, the Catholic nun and missionary renowned for her charitable work with the poor in Kolkata, India.
  • E. Paola
    Paola is an Italian noblewoman who became Queen consort of Belgium as the wife of King Albert II.
  • 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: Fátima
Triple: [Marian apparitions at Fatima, hasLocation, Fátima]
Generated description
Fátima is a town in central Portugal renowned as a major Catholic pilgrimage site associated with reported Marian apparitions in 1917.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Fátima
Target entity description: Fátima is a town in central Portugal renowned as a major Catholic pilgrimage site associated with reported Marian apparitions in 1917.
  • A. María
    María is a key character in Ernest Hemingway's novel "For Whom the Bell Tolls," known as a young Spanish woman and love interest of the protagonist amid the Spanish Civil War.
  • B. Francisca
    Francisca is a feminine given name, used in various European and Latin American cultures, that is cognate with the English name Frances.
  • C. Belén
    Belén is a town in northwestern Argentina known for its traditional weaving and role as a regional center in Catamarca Province.
  • D. Teresa
    Teresa is the religious name of Mother Teresa, the Catholic nun and missionary renowned for her charitable work with the poor in Kolkata, India.
  • E. Paola
    Paola is an Italian noblewoman who became Queen consort of Belgium as the wife of King Albert II.
  • 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_69a4939c32488190a7ccd41cf0abb22b completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ace8b8688190ac065f92c017adec completed March 1, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7c021732c8190a3b4020f8e3cb90e completed March 4, 2026, 5:16 a.m.
NEDg Description generation batch_69a7c0f4bd348190a5c258650a92958a completed March 4, 2026, 5:19 a.m.
NED2 Entity disambiguation (via description) batch_69a7c206d5c481908f45fcf9b94eec14 completed March 4, 2026, 5:24 a.m.
Created at: March 1, 2026, 7:39 p.m.