Triple

T3608718
Position Surface form Disambiguated ID Type / Status
Subject Centro Region E76433 entity
Predicate containsCity P294 FINISHED
Object Fátima E105859 NE FINISHED

How this triple was built (2 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: [Centro Region, containsCity, Fátima]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fátima
Context triple: [Centro Region, containsCity, Fátima]
  • A. Fátima chosen
    Fátima is a town in central Portugal renowned as a major Catholic pilgrimage site associated with reported Marian apparitions in 1917.
  • B. 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.
  • C. María
    "María" is a film featuring actress Taryn Power in a significant role.
  • D. Amparo
    Amparo is a municipality in the interior of Brazil known for its historical architecture and role in the coffee-producing region of the state of São Paulo.
  • E. Francisca
    Francisca is a feminine given name, used in various European and Latin American cultures, that is cognate with the English name Frances.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ad85da0ba481908b3b48c69efe2b98 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc22a3cf081908c20b6fb55be0db2 completed March 8, 2026, 6:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4330de7a08190933aa7e9dc0a65be completed March 13, 2026, 3:53 p.m.
Created at: March 8, 2026, 3:22 p.m.