Triple

T16828006
Position Surface form Disambiguated ID Type / Status
Subject Cañas y barro E409070 entity
Predicate mainCharacter P1183 FINISHED
Object Neleta
Neleta is a central character in Vicente Blasco Ibáñez’s novel "Cañas y barro," embodying the social and emotional tensions of life in the Albufera region of Valencia.
 E1235394 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: Neleta | Statement: [Cañas y barro, mainCharacter, Neleta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Neleta
Context triple: [Cañas y barro, mainCharacter, Neleta]
  • A. Rosanna
    Rosanna is a residential suburb in Melbourne, Australia, known for its leafy streets, family-friendly atmosphere, and proximity to parklands and public transport.
  • B. Rosanna
    Rosanna is a feminine given name of Latin origin, derived from a combination of "Rose" and "Anna."
  • C. La Nena
    "La Nena" is a song featured on the album "Quizás" by Spanish singer-songwriter Enrique Iglesias.
  • D. Amoreena
    "Amoreena" is a song by Elton John, featured on his 1970 album *Tumbleweed Connection*, known for its country-rock style and vivid storytelling lyrics.
  • E. Nena
    Nena is a German pop singer and actress best known internationally for her 1983 hit song "99 Luftballons."
  • 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: Neleta
Triple: [Cañas y barro, mainCharacter, Neleta]
Generated description
Neleta is a central character in Vicente Blasco Ibáñez’s novel "Cañas y barro," embodying the social and emotional tensions of life in the Albufera region of Valencia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Neleta
Target entity description: Neleta is a central character in Vicente Blasco Ibáñez’s novel "Cañas y barro," embodying the social and emotional tensions of life in the Albufera region of Valencia.
  • A. Rosanna
    Rosanna is a residential suburb in Melbourne, Australia, known for its leafy streets, family-friendly atmosphere, and proximity to parklands and public transport.
  • B. Rosanna
    Rosanna is a feminine given name of Latin origin, derived from a combination of "Rose" and "Anna."
  • C. La Nena
    "La Nena" is a song featured on the album "Quizás" by Spanish singer-songwriter Enrique Iglesias.
  • D. Amoreena
    "Amoreena" is a song by Elton John, featured on his 1970 album *Tumbleweed Connection*, known for its country-rock style and vivid storytelling lyrics.
  • E. Nena
    Nena is a German pop singer and actress best known internationally for her 1983 hit song "99 Luftballons."
  • 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_69d88394566c8190b3dcbdc72935f7fa completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b3151350819097b1c375e6df8986 completed April 18, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00b2a0ac148190a7a7edebcb67c040 completed May 10, 2026, 4:30 p.m.
NEDg Description generation batch_6a00b35ea8f88190ae33e8a2f906d133 completed May 10, 2026, 4:33 p.m.
NED2 Entity disambiguation (via description) batch_6a00b3d14b3c819081f435777f47eca3 completed May 10, 2026, 4:35 p.m.
Created at: April 10, 2026, 5:23 a.m.