Triple

T8708226
Position Surface form Disambiguated ID Type / Status
Subject Timescape E206704 entity
Predicate hasCharacter P2308 FINISHED
Object Penny
Penny is a fictional character appearing in the science fiction novel "Timescape" by Gregory Benford.
 E753581 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: Penny | Statement: [Timescape, hasCharacter, Penny]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Penny
Context triple: [Timescape, hasCharacter, Penny]
  • A. Penny
    Penny is a friendly, aspiring actress and waitress who becomes the sociable, down-to-earth neighbor and later close friend and love interest of the main nerdy characters in the sitcom "The Big Bang Theory."
  • B. Penny
    Penny is the given name of American actress Penny Johnson Jerald, known for her roles in series such as "24" and "Star Trek: Deep Space Nine."
  • C. Penny
    Penny is the brave young orphan girl who is rescued by mice in Disney's animated adventure film "The Rescuers."
  • D. Penny
    Penny Pritzker is an American billionaire businesswoman, civic leader, and former U.S. Secretary of Commerce in the Obama administration.
  • E. Penny
    Penny is a character in Jim Jarmusch’s film "Broken Flowers," one of the former lovers visited by the protagonist during his cross-country journey.
  • 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: Penny
Triple: [Timescape, hasCharacter, Penny]
Generated description
Penny is a fictional character appearing in the science fiction novel "Timescape" by Gregory Benford.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Penny
Target entity description: Penny is a fictional character appearing in the science fiction novel "Timescape" by Gregory Benford.
  • A. Penny
    Penny is a character in Jim Jarmusch’s film "Broken Flowers," one of the former lovers visited by the protagonist during his cross-country journey.
  • B. Penny
    Penny is the given name of American actress Penny Johnson Jerald, known for her roles in series such as "24" and "Star Trek: Deep Space Nine."
  • C. Penny
    Penny is a friendly, aspiring actress and waitress who becomes the sociable, down-to-earth neighbor and later close friend and love interest of the main nerdy characters in the sitcom "The Big Bang Theory."
  • D. Penny
    Penny is the brave young orphan girl who is rescued by mice in Disney's animated adventure film "The Rescuers."
  • E. Penny
    Penny is the nickname of Anfernee "Penny" Hardaway, a former NBA All-Star guard and current college basketball coach known for his dynamic playmaking and scoring in the 1990s.
  • 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_69ca835645e881908f00e3c8b51da81d completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc58ffa6a481908866b6239d1d9b92 completed March 31, 2026, 11:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf28b78e90819098ab1d4877ab88fe completed April 3, 2026, 2:40 a.m.
NEDg Description generation batch_69cf2bd14c3c8190b43840ee57cca22c completed April 3, 2026, 2:54 a.m.
NED2 Entity disambiguation (via description) batch_69cf2cb3c4308190971fb3d25064f205 completed April 3, 2026, 2:57 a.m.
Created at: March 30, 2026, 6:35 p.m.