Triple

T21534610
Position Surface form Disambiguated ID Type / Status
Subject Ana María Matute E531318 entity
Predicate notableWork P4 FINISHED
Object Aranmanoth
Aranmanoth is a lyrical, medieval-set novel by Spanish author Ana María Matute that explores themes of childhood, identity, and the loss of innocence.
 E1488524 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: Aranmanoth | Statement: [Ana María Matute, notableWork, Aranmanoth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Aranmanoth
Context triple: [Ana María Matute, notableWork, Aranmanoth]
  • A. Mooanam
    Mooanam was a member of the Wampanoag royal family, known primarily as one of the children of the influential sachem Massasoit in early 17th-century New England.
  • B. Arunan
    Arunan is a given name, notably borne by individuals such as Arunan Arulampalam.
  • C. Aranoch
    Aranoch is a vast desert region in the Diablo universe, known for its harsh climate, ancient ruins, and cities like Lut Gholein.
  • D. Talibon
    Talibon is a coastal municipality in the northern part of Bohol in the Philippines, known for its rich marine resources and fishing industry.
  • E. Marangona
    Marangona is the largest and most famous bell of St Mark's Campanile in Venice, traditionally used to mark the beginning and end of the working day and to signal important civic events.
  • 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: Aranmanoth
Triple: [Ana María Matute, notableWork, Aranmanoth]
Generated description
Aranmanoth is a lyrical, medieval-set novel by Spanish author Ana María Matute that explores themes of childhood, identity, and the loss of innocence.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Aranmanoth
Target entity description: Aranmanoth is a lyrical, medieval-set novel by Spanish author Ana María Matute that explores themes of childhood, identity, and the loss of innocence.
  • A. Mooanam
    Mooanam was a member of the Wampanoag royal family, known primarily as one of the children of the influential sachem Massasoit in early 17th-century New England.
  • B. Arunan
    Arunan is a given name, notably borne by individuals such as Arunan Arulampalam.
  • C. Aranoch
    Aranoch is a vast desert region in the Diablo universe, known for its harsh climate, ancient ruins, and cities like Lut Gholein.
  • D. Talibon
    Talibon is a coastal municipality in the northern part of Bohol in the Philippines, known for its rich marine resources and fishing industry.
  • E. Marangona
    Marangona is the largest and most famous bell of St Mark's Campanile in Venice, traditionally used to mark the beginning and end of the working day and to signal important civic events.
  • 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_69e0c45e5b8881908ac18fc2f493b114 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ee9d0b9888819094e424d33c14d5d0 completed April 26, 2026, 11:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a09e8339c04819092968f7a7baba3f8 completed May 17, 2026, 4:09 p.m.
NEDg Description generation batch_6a09e918bc80819093a8939e0eabf06f completed May 17, 2026, 4:13 p.m.
NED2 Entity disambiguation (via description) batch_6a09e98b27ec8190bacd93a48e4d5467 completed May 17, 2026, 4:15 p.m.
Created at: April 16, 2026, 6:27 p.m.