Triple

T14704980
Position Surface form Disambiguated ID Type / Status
Subject The Jungle E345404 entity
Predicate mainCharacter P1183 FINISHED
Object Teta Elzbieta
Teta Elzbieta is a key supporting figure in Upton Sinclair’s novel "The Jungle," representing the struggles and resilience of an immigrant family in early 20th-century Chicago.
 E1116107 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: Teta Elzbieta | Statement: [The Jungle, mainCharacter, Teta Elzbieta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Teta Elzbieta
Context triple: [The Jungle, mainCharacter, Teta Elzbieta]
  • A. Thereza
    Thereza is a given name, most commonly a variant spelling of Theresa used as a feminine first name in various cultures.
  • B. Beata
    Beata is a feminine given name of Latin origin, commonly used in various European countries and meaning "blessed" or "happy."
  • C. Matylda
    Matylda is a feminine given name, commonly used in Central and Eastern Europe, that is a variant of the name Matilda.
  • D. Eugénia
    Eugénia is a given name, commonly used in Portuguese and other Romance languages, that is a variant of the name Eugenia.
  • E. Zita
    Zita is a feminine given name of European origin, notably borne by the Austrian-American actress Zita Johann.
  • 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: Teta Elzbieta
Triple: [The Jungle, mainCharacter, Teta Elzbieta]
Generated description
Teta Elzbieta is a key supporting figure in Upton Sinclair’s novel "The Jungle," representing the struggles and resilience of an immigrant family in early 20th-century Chicago.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Teta Elzbieta
Target entity description: Teta Elzbieta is a key supporting figure in Upton Sinclair’s novel "The Jungle," representing the struggles and resilience of an immigrant family in early 20th-century Chicago.
  • A. Thereza
    Thereza is a given name, most commonly a variant spelling of Theresa used as a feminine first name in various cultures.
  • B. Beata
    Beata is a feminine given name of Latin origin, commonly used in various European countries and meaning "blessed" or "happy."
  • C. Matylda
    Matylda is a feminine given name, commonly used in Central and Eastern Europe, that is a variant of the name Matilda.
  • D. Eugénia
    Eugénia is a given name, commonly used in Portuguese and other Romance languages, that is a variant of the name Eugenia.
  • E. Zita
    Zita is a feminine given name of European origin, notably borne by the Austrian-American actress Zita Johann.
  • 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_69d822e4a8c08190a155df736bb7bc13 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb6086c608190a66c64e23a3e002f completed April 14, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdf087ce8c819081a7186df67bcf1f completed May 8, 2026, 2:17 p.m.
NEDg Description generation batch_69fdf2a63cc88190b3670378c54c96b6 completed May 8, 2026, 2:26 p.m.
NED2 Entity disambiguation (via description) batch_69fdf31fcb4081908a88cf4d4c5ddced completed May 8, 2026, 2:28 p.m.
Created at: April 10, 2026, 1:28 a.m.