Triple

T23162589
Position Surface form Disambiguated ID Type / Status
Subject Sierra de Cádiz E578625 entity
Predicate contains P35 FINISHED
Object Espera
Espera is a small historic town in the province of Cádiz in southern Spain, known for its whitewashed houses, hilltop castle, and surrounding rural landscapes.
E1575299 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: Espera | Statement: [Sierra de Cádiz, contains, Espera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Espera
Context triple: [Sierra de Cádiz, contains, Espera]
  • A. Esper
    Esper is a surname most prominently associated with Mark Esper, the former U.S. Secretary of Defense under President Donald Trump.
  • B. Esperança
    Esperança is a Brazilian telenovela in which actress Giselle Itié gained prominence for one of her most recognized roles.
  • C. Esperih
    Esperih is another name for Asparuh of Bulgaria, the 7th-century Bulgar ruler who founded the First Bulgarian Empire in the Balkans.
  • D. Esperanza
    Esperanza is a municipality located in the province of Sultan Kudarat in the Philippines, known for its agricultural economy and diverse cultural communities.
  • E. Esperanza
    "Esperanza" is a romantic Latin pop ballad best known as the signature hit from the album *Cosas del Amor*.
  • 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: Espera
Triple: [Sierra de Cádiz, contains, Espera]
Generated description
Espera is a small historic town in the province of Cádiz in southern Spain, known for its whitewashed houses, hilltop castle, and surrounding rural landscapes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Espera
Target entity description: Espera is a small historic town in the province of Cádiz in southern Spain, known for its whitewashed houses, hilltop castle, and surrounding rural landscapes.
  • A. Esper
    Esper is a surname most prominently associated with Mark Esper, the former U.S. Secretary of Defense under President Donald Trump.
  • B. Esperança
    Esperança is a Brazilian telenovela in which actress Giselle Itié gained prominence for one of her most recognized roles.
  • C. Esperih
    Esperih is another name for Asparuh of Bulgaria, the 7th-century Bulgar ruler who founded the First Bulgarian Empire in the Balkans.
  • D. Esperanza
    "Esperanza" is a romantic Latin pop ballad best known as the signature hit from the album *Cosas del Amor*.
  • E. Esperanza
    Esperanza is a municipality located in the province of Sultan Kudarat in the Philippines, known for its agricultural economy and diverse cultural communities.
  • 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_69e245fc75348190a0288401044c8af8 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18f019cd881908e3c68d99454da2a completed April 29, 2026, 4:54 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c30a21a548190add77bc839424eb3 completed May 19, 2026, 9:42 a.m.
NEDg Description generation batch_6a0c330135cc8190b5a0e512bda6277d completed May 19, 2026, 9:53 a.m.
NED2 Entity disambiguation (via description) batch_6a0c375dd5a4819097a80ae43a1c4442 completed May 19, 2026, 10:11 a.m.
Created at: April 17, 2026, 4:02 p.m.