Triple

T8730466
Position Surface form Disambiguated ID Type / Status
Subject North Jersey E207241 entity
Predicate hasMajorCity P316 FINISHED
Object Elizabeth
Elizabeth is a major city in northeastern New Jersey known as an important industrial, transportation, and commercial hub near Newark and New York City.
 E55624 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: Elizabeth | Statement: [North Jersey, hasMajorCity, Elizabeth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Elizabeth
Context triple: [North Jersey, hasMajorCity, Elizabeth]
  • A. Elizabeth
    Elizabeth is the middle name of Lady Sarah Chatto, a British painter and member of the extended royal family.
  • B. Elizabeth
    "Elizabeth" is a popular country and gospel song by The Statler Brothers, known for its rich harmonies and storytelling lyrics.
  • C. Elizabeth
    Elizabeth is the given first name of American silent film actress Betty Bronson, known for her role as Peter Pan in the 1924 film adaptation.
  • D. Elizabeth
    Elizabeth is the central protagonist of the interactive narrative game "If/Then," around whom the story’s key choices and emotional developments revolve.
  • E. Elizabeth
    Elizabeth is the central character in the Broadway musical "If/Then," a woman who explores how a single choice can lead to radically different life paths.
  • 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: Elizabeth
Triple: [North Jersey, hasMajorCity, Elizabeth]
Generated description
Elizabeth is a major city in northeastern New Jersey known as an important industrial, transportation, and commercial hub near Newark and New York City.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Elizabeth
Target entity description: Elizabeth is a major city in northeastern New Jersey known as an important industrial, transportation, and commercial hub near Newark and New York City.
  • A. Elizabeth chosen
    Elizabeth is a city in northeastern New Jersey that forms part of the greater New York metropolitan area.
  • B. Elizabeth
    Elizabeth is a suburban electorate in South Australia known for its working-class community and industrial heritage within the northern Adelaide region.
  • C. Elizabeth
    Elizabeth is the first name of Elizabeth Warren, a prominent American politician and U.S. senator from Massachusetts known for her work on consumer protection and economic inequality.
  • D. Elizabeth
    Elizabeth is a biblical figure in the New Testament, known as the mother of John the Baptist and a relative of Mary, the mother of Jesus.
  • E. Elizabeth
    Elizabeth is a feminine given name of Hebrew origin, traditionally interpreted to mean "God is my oath" and widely used in many English-speaking and European cultures.
  • F. None of above.

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_69ca8358e4008190898471a59b96c301 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d26d280819085e15d4917c2b9a5 completed March 31, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf2923abc48190a5b6027c2e4f1db7 completed April 3, 2026, 2:42 a.m.
NEDg Description generation batch_69cf2bd42e6081908e016303eeb2241f completed April 3, 2026, 2:54 a.m.
NED2 Entity disambiguation (via description) batch_69cf2ce47b748190b883063dc3e5d16b completed April 3, 2026, 2:58 a.m.
Created at: March 30, 2026, 6:37 p.m.