Triple

T23308841
Position Surface form Disambiguated ID Type / Status
Subject Amon, king of Judah E590525 entity
Predicate biblicalBookMentionedIn P5309 FINISHED
Object Matthew
Matthew is a New Testament Gospel that recounts the life, teachings, death, and resurrection of Jesus Christ, emphasizing his fulfillment of Old Testament prophecy.
E1581640 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: Matthew | Statement: [Amon, king of Judah, biblicalBookMentionedIn, Matthew]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matthew
Context triple: [Amon, king of Judah, biblicalBookMentionedIn, Matthew]
  • A. John
    John is the given name of John D. Rockefeller, the American industrialist and philanthropist who founded Standard Oil and became one of the wealthiest individuals in history.
  • B. John
    John is the given name of John W. Mauchly, the American physicist and co-inventor of the ENIAC computer.
  • C. John
    John is the given first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
  • D. John
    John is the given name of John Albert William Spencer-Churchill, a British aristocrat and 10th Duke of Marlborough.
  • E. John
    John is the given name of John Romita Sr., the influential American comic book artist best known for his work on Marvel's The Amazing Spider-Man.
  • 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: Matthew
Triple: [Amon, king of Judah, biblicalBookMentionedIn, Matthew]
Generated description
Matthew is a New Testament Gospel that recounts the life, teachings, death, and resurrection of Jesus Christ, emphasizing his fulfillment of Old Testament prophecy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Matthew
Target entity description: Matthew is a New Testament Gospel that recounts the life, teachings, death, and resurrection of Jesus Christ, emphasizing his fulfillment of Old Testament prophecy.
  • A. Matthew
    Matthew is traditionally recognized as one of the Twelve Apostles of Jesus and is commonly associated with the authorship of the Gospel of Matthew in the New Testament.
  • B. Matthew
    Matthew is a masculine given name of Hebrew origin, commonly used in English-speaking countries and meaning "gift of God."
  • C. Matthew
    Matthew is a person known primarily as Lisa's romantic partner.
  • D. Matthew
    Matthew is the central protagonist of the film "Wicker Park," whose obsessive search for a lost love drives the movie’s intricate romantic mystery.
  • E. Matthew
    Matthew is a fictional character played by American actor Jonathan Brandis, best known for his roles in 1990s film and television.
  • 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_69e25d1d32188190948eb76909d1dcc3 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f197292fd08190bc364e1433dde213 completed April 29, 2026, 5:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c4c9e2f4c8190a7b7c89805d85745 completed May 19, 2026, 11:42 a.m.
NEDg Description generation batch_6a0c4fd38fa48190958edaece1496a94 completed May 19, 2026, 11:56 a.m.
NED2 Entity disambiguation (via description) batch_6a0c506b25ec819084b9522fa827abe7 completed May 19, 2026, 11:58 a.m.
Created at: April 17, 2026, 5:05 p.m.