Triple

T25508778
Position Surface form Disambiguated ID Type / Status
Subject Penelope Devereux E639314 entity
Predicate literaryCharacterModeledAs P162887 FINISHED
Object Stella
Stella is the idealized beloved in Sir Philip Sidney’s sonnet sequence "Astrophil and Stella," widely thought to be modeled on the Elizabethan noblewoman Penelope Devereux.
 E639313 NE FINISHED

How this triple was built (3 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: Stella | Statement: [Penelope Devereux, literaryCharacterModeledAs, Stella]
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: Stella
Triple: [Penelope Devereux, literaryCharacterModeledAs, Stella]
Generated description
Stella is the idealized beloved in Sir Philip Sidney’s sonnet sequence "Astrophil and Stella," widely thought to be modeled on the Elizabethan noblewoman Penelope Devereux.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: literaryCharacterModeledAs
Context triple: [Penelope Devereux, literaryCharacterModeledAs, Stella]
  • A. fictionalCharacter
    Indicates that one entity is a fictional character that appears within the narrative world of another entity (such as a work, series, or franchise).
  • B. fictionalCharacterAssisted
    Indicates that one fictional character provided help, support, or assistance to another fictional character.
  • C. literaryRole
    Indicates the specific narrative or functional role an entity holds within a literary work or text.
  • D. fictionalCharacterFrom
    Indicates that a fictional character originates from, or is created within, a particular work, universe, or source.
  • E. storyCharacterizedAs
    Indicates that a story is described, portrayed, or defined as having a particular quality, style, or attribute.
  • F. None of above. chosen

Provenance (7 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_69e75dbd09308190b6b5f0afdc12ec6d completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f62e83045c8190a424a2e401a88e9e completed May 2, 2026, 5:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ad7d5c1081908f7658de29362c5b completed May 22, 2026, 7:24 p.m.
NEDg Description generation batch_6a10ae7ea0088190bdefa7c31fe2859d completed May 22, 2026, 7:29 p.m.
NED2 Entity disambiguation (via description) batch_6a10af719e6c8190bbd23598b3426106 completed May 22, 2026, 7:33 p.m.
PD Predicate disambiguation batch_69f62c1379f08190836c3e02b0c892df completed May 2, 2026, 4:53 p.m.
PDg Predicate description generation batch_69f62d886828819080ec2f742b9449e3 completed May 2, 2026, 4:59 p.m.
Created at: April 21, 2026, 2:48 p.m.