Triple

T1752248
Position Surface form Disambiguated ID Type / Status
Subject Kingdom of Navarre E38469 entity
Predicate majorCity P316 FINISHED
Object Estella
Estella is a historic town in northern Spain, renowned as an important stop on the Camino de Santiago pilgrimage route and for its well-preserved medieval architecture.
 E196540 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: Estella | Statement: [Kingdom of Navarre, majorCity, Estella]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Estella
Context triple: [Kingdom of Navarre, majorCity, Estella]
  • A. Belén
    Belén is a town in northwestern Argentina known for its traditional weaving and role as a regional center in Catamarca Province.
  • B. Valdemoro
    Valdemoro is a municipality and growing suburban town in central Spain, located south of Madrid.
  • C. Pilar
    Pilar is a strong-willed, perceptive Spanish guerrilla fighter who plays a central role in Ernest Hemingway’s novel "For Whom the Bell Tolls."
  • D. Pilar
    Pilar is a riverside city in southwestern Paraguay known for its colonial architecture, river port activities, and proximity to the border with Argentina.
  • E. Pilar
    Pilar is the introspective female protagonist of Paulo Coelho’s novel "By the River Piedra I Sat Down and Wept," whose spiritual and emotional journey drives the story.
  • 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: Estella
Triple: [Kingdom of Navarre, majorCity, Estella]
Generated description
Estella is a historic town in northern Spain, renowned as an important stop on the Camino de Santiago pilgrimage route and for its well-preserved medieval architecture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Estella
Target entity description: Estella is a historic town in northern Spain, renowned as an important stop on the Camino de Santiago pilgrimage route and for its well-preserved medieval architecture.
  • A. Belén
    Belén is a town in northwestern Argentina known for its traditional weaving and role as a regional center in Catamarca Province.
  • B. Valdemoro
    Valdemoro is a municipality and growing suburban town in central Spain, located south of Madrid.
  • C. Pilar
    Pilar is a strong-willed, perceptive Spanish guerrilla fighter who plays a central role in Ernest Hemingway’s novel "For Whom the Bell Tolls."
  • D. Pilar
    Pilar is a riverside city in southwestern Paraguay known for its colonial architecture, river port activities, and proximity to the border with Argentina.
  • E. Pilar
    Pilar is the introspective female protagonist of Paulo Coelho’s novel "By the River Piedra I Sat Down and Wept," whose spiritual and emotional journey drives the story.
  • 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_69a8862bdb2081908aefe831c8aa8017 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa641432d88190ab4254cb4c3ad402 completed March 6, 2026, 5:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada0e625c48190a0fbda31010bdc5f completed March 8, 2026, 4:16 p.m.
NEDg Description generation batch_69ada1e13d408190b393c00c331125a2 completed March 8, 2026, 4:20 p.m.
NED2 Entity disambiguation (via description) batch_69ada292a34c8190a566c2909342ab27 completed March 8, 2026, 4:23 p.m.
Created at: March 4, 2026, 7:31 p.m.