Triple

T3795322
Position Surface form Disambiguated ID Type / Status
Subject Jessica Lange E89755 entity
Predicate givenName P17 FINISHED
Object 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."
 E391589 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: [Jessica Lange, givenName, Jessica]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jessica
Context triple: [Jessica Lange, givenName, 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 women's fashion and apparel brand that was sold exclusively through Sears Canada.
  • C. Jessica
    Jessica is a kind-hearted schoolteacher who becomes Mrs. Claus in the classic stop-motion Christmas special "Santa Claus Is Comin' to Town."
  • D. Emily
    Emily is a given name commonly used in English-speaking countries, often associated with literary, historical, and contemporary cultural figures.
  • E. Emily
    Emily Warren Roebling was a pioneering 19th-century American engineer best known for her crucial role in overseeing the completion of the Brooklyn Bridge.
  • 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: [Jessica Lange, givenName, Jessica]
Generated description
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."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jessica
Target entity description: 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."
  • 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. Emily
    Emily is a given name commonly used in English-speaking countries, often associated with literary, historical, and contemporary cultural figures.
  • E. Emily
    Emily Warren Roebling was a pioneering 19th-century American engineer best known for her crucial role in overseeing the completion of the Brooklyn Bridge.
  • 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_69aed9597d6881909b6ee3b9de859223 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aee79db2e88190b3aa2b8e8d885e19 completed March 9, 2026, 3:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4fb232650819089feed9d5bb8c91a completed March 14, 2026, 6:07 a.m.
NEDg Description generation batch_69b4fc7abfb481908f563e17e6e57a4e completed March 14, 2026, 6:13 a.m.
NED2 Entity disambiguation (via description) batch_69b4fce0a6a88190be19941a70caebdc completed March 14, 2026, 6:14 a.m.
Created at: March 9, 2026, 3:15 p.m.