Triple

T12122453
Position Surface form Disambiguated ID Type / Status
Subject Bielsa E288726 entity
Predicate hasRegion P285 FINISHED
Object High Aragon E555123 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: High Aragon | Statement: [Bielsa, hasRegion, High Aragon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: High Aragon
Context triple: [Bielsa, hasRegion, High Aragon]
  • A. Aragunnu
    Aragunnu is a coastal area within Mimosa Rocks National Park in New South Wales, Australia, known for its scenic beaches, rocky headlands, and Aboriginal cultural sites.
  • B. Gisondo
    Gisondo is an Italian-origin surname most notably borne by American actor Skyler Gisondo.
  • C. Aínsa chosen
    Aínsa is a historic medieval town in northeastern Spain, renowned for its well-preserved old quarter and hilltop castle overlooking the Pyrenees.
  • D. Semprún
    Semprún is the surname of Jorge Semprún, the Spanish-born writer, politician, and Holocaust survivor known for his works on exile, memory, and totalitarianism.
  • E. Aranzazu
    Aranzazu is a small Colombian town located in the mountainous coffee-growing region of the Caldas Department.
  • 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_69d6ab4b5e4c81909950b17151eb0951 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d91578fd88819099adf55c93d549fc completed April 10, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f684172c81908b77daa243dc8ed8 completed May 2, 2026, 1:05 p.m.
Created at: April 8, 2026, 9:49 p.m.