Triple

T3593576
Position Surface form Disambiguated ID Type / Status
Subject Sears Canada E76082 entity
Predicate brand P1500 FINISHED
Object Jessica
Jessica is a women's fashion and apparel brand that was sold exclusively through Sears Canada.
 E376227 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: [Sears Canada, brand, Jessica]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jessica
Context triple: [Sears Canada, brand, 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. 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.
  • D. Emily
    Emily is a given name commonly used in English-speaking countries, often associated with literary, historical, and contemporary cultural figures.
  • E. Sarah
    Sarah is the central protagonist of the story "Horse Girl," around whom the main narrative and character development revolve.
  • 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: [Sears Canada, brand, Jessica]
Generated description
Jessica is a women's fashion and apparel brand that was sold exclusively through Sears Canada.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jessica
Target entity description: Jessica is a women's fashion and apparel brand that was sold exclusively through Sears Canada.
  • 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. Emily
    Emily is a given name commonly used in English-speaking countries, often associated with literary, historical, and contemporary cultural figures.
  • D. 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.
  • E. Sarah
    Sarah is the central protagonist of the story "Horse Girl," around whom the main narrative and character development revolve.
  • 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_69ad85d8042081908af94a04c410dec0 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc15bbbcc81908d6cf95f8e70c6ca completed March 8, 2026, 6:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69b44efeacf481908dd9a26f348f9977 completed March 13, 2026, 5:53 p.m.
NEDg Description generation batch_69b453c225b481908cc06090bcd0ed64 completed March 13, 2026, 6:13 p.m.
NED2 Entity disambiguation (via description) batch_69b45f6aefd081909dfd1740f233dbf3 completed March 13, 2026, 7:03 p.m.
Created at: March 8, 2026, 3:22 p.m.