Triple

T13052822
Position Surface form Disambiguated ID Type / Status
Subject Mattea E327488 entity
Predicate derivedFrom P909 FINISHED
Object Matthew
Matthew is a common male given name of Hebrew origin, widely known from the New Testament apostle and Gospel writer.
E556162 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: [Mattea, derivedFrom, Matthew]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matthew
Context triple: [Mattea, derivedFrom, Matthew]
  • A. John
    John is traditionally regarded as the author of the New Testament’s Book of Revelation, a prophetic and apocalyptic text in Christian scripture.
  • B. John
    John is the given name of the late American comedian and actor John Belushi, famed for his work on "Saturday Night Live" and in films like "Animal House" and "The Blues Brothers."
  • C. John
    John is the given name of John A. Macdonald, the first prime minister of Canada and a key figure in the country's Confederation.
  • D. John
    John is the given name of John M. Grunsfeld, an American physicist, former NASA astronaut, and leader in space science and exploration.
  • E. John
    John II Casimir Vasa was a 17th-century King of Poland and Grand Duke of Lithuania from the Swedish House of Vasa.
  • 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: [Mattea, derivedFrom, Matthew]
Generated description
Matthew is a common male given name of Hebrew origin, widely known from the New Testament apostle and Gospel writer.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Matthew
Target entity description: Matthew is a common male given name of Hebrew origin, widely known from the New Testament apostle and Gospel writer.
  • A. Matthew chosen
    Matthew is a masculine given name of Hebrew origin, commonly used in English-speaking countries and meaning "gift of God."
  • B. 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.
  • C. Matthew
    Matthew is the given name of Sir Matt Busby, the legendary Scottish football manager best known for his long and successful tenure at Manchester United.
  • D. Matthew
    Matthew is the full given name of American television journalist and former "Today" show co-host Matt Lauer.
  • E. Matthew
    Matthew is the given name of the pioneering British Egyptologist and archaeologist Flinders Petrie, renowned for developing systematic excavation and seriation methods.
  • 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_69d8076e64308190904fb5c93517c901 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d980b98fa081908cfa92116799e874 completed April 10, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d5ff8c308190a40274c68a1c5da3 completed May 3, 2026, 4:58 a.m.
NEDg Description generation batch_69f6d8c8a8b48190a2dc2f6b5e7d37e0 completed May 3, 2026, 5:10 a.m.
NED2 Entity disambiguation (via description) batch_69f6d98d6ba48190b63f6330ba215c36 completed May 3, 2026, 5:13 a.m.
Created at: April 9, 2026, 8:58 p.m.