Triple

T13568777
Position Surface form Disambiguated ID Type / Status
Subject Dirty Hands E324104 entity
Predicate hasCharacter P2308 FINISHED
Object Jessica
Jessica is a character from the science fiction novel "Dirty Hands," likely involved in its morally complex, politically charged narrative.
 E1049729 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: Jessica | Statement: [Dirty Hands, hasCharacter, Jessica]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jessica
Context triple: [Dirty Hands, hasCharacter, Jessica]
  • A. Jessica
    Jessica Barth is an American actress best known for her comedic role as Tami-Lynn in the "Ted" film series.
  • B. Jessica
    Jessica is a kind-hearted schoolteacher who becomes Mrs. Claus in the classic stop-motion Christmas special "Santa Claus Is Comin' to Town."
  • C. Jessica
    Jessica is a women's fashion and apparel brand that was sold exclusively through Sears Canada.
  • D. Jessica
    Jessica is a feminine given name of Hebrew origin, widely used in English-speaking countries and popularized by Shakespeare’s play "The Merchant of Venice."
  • E. Emily
    Emily is a given name commonly used in English-speaking countries, often associated with literary, historical, and contemporary cultural figures.
  • 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: Jessica
Triple: [Dirty Hands, hasCharacter, Jessica]
Generated description
Jessica is a character from the science fiction novel "Dirty Hands," likely involved in its morally complex, politically charged narrative.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jessica
Target entity description: Jessica is a character from the science fiction novel "Dirty Hands," likely involved in its morally complex, politically charged narrative.
  • A. Jessica
    Jessica Barth is an American actress best known for her comedic role as Tami-Lynn in the "Ted" film series.
  • B. Jessica
    Jessica is a kind-hearted schoolteacher who becomes Mrs. Claus in the classic stop-motion Christmas special "Santa Claus Is Comin' to Town."
  • C. Jessica
    Jessica is a women's fashion and apparel brand that was sold exclusively through Sears Canada.
  • D. Jessica
    Jessica is a feminine given name of Hebrew origin, widely used in English-speaking countries and popularized by Shakespeare’s play "The Merchant of Venice."
  • E. Emily
    Emily is a given name commonly used in English-speaking countries, often associated with literary, historical, and contemporary cultural figures.
  • 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_69d8076830b48190910a902bae5888e2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb00e0188819094fde44f85adb69c completed April 12, 2026, 2:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76bb3d77c8190a7af2ee7e9b6748a completed May 3, 2026, 3:37 p.m.
NEDg Description generation batch_69f77640b5308190aaa50e8d5d871832 completed May 3, 2026, 4:22 p.m.
NED2 Entity disambiguation (via description) batch_69f779178dc48190bb0de790de30d8b0 completed May 3, 2026, 4:34 p.m.
Created at: April 9, 2026, 9:48 p.m.