Triple
T12386014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matthew Holworthy |
E295865
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object |
Matthew
Matthew is a common masculine given name of Hebrew origin, widely used in English-speaking countries.
|
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: [Matthew Holworthy, hasGivenName, Matthew]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matthew Context triple: [Matthew Holworthy, hasGivenName, Matthew]
-
A.
John
John is the given first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
-
B.
John
John is the given name of John Randolph Hearst, a member of the prominent Hearst family associated with American media and publishing.
-
C.
John
John Stallworth is a former American football wide receiver best known for his Hall of Fame career with the Pittsburgh Steelers during their 1970s dynasty.
-
D.
John
John "Jack" Pfiester was an early 20th-century American Major League Baseball pitcher, best known for his standout seasons with the Chicago Cubs during their dominant era.
-
E.
John
John G. Kemeny was a Hungarian-American mathematician and computer scientist best known as the co-inventor of the BASIC programming language and former president of Dartmouth College.
- 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: [Matthew Holworthy, hasGivenName, Matthew]
Generated description
Matthew is a common masculine given name of Hebrew origin, widely used in English-speaking countries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Matthew Target entity description: Matthew is a common masculine given name of Hebrew origin, widely used in English-speaking countries.
-
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 the given name of Sir Matt Busby, the legendary Scottish football manager best known for his long and successful tenure at Manchester United.
-
C.
Matthew
Matthew is the full given name of American television journalist and former "Today" show co-host Matt Lauer.
-
D.
Matthew
Matthew is the given name of the pioneering British Egyptologist and archaeologist Flinders Petrie, renowned for developing systematic excavation and seriation methods.
-
E.
Matthew
Matthew is the full given name of American former professional stock car racing driver Matt Kenseth, a NASCAR Cup Series champion.
- 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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d93fbd489c819098233a111442762e |
completed | April 10, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62ac939bc819081629b9eef20c4e7 |
completed | May 2, 2026, 4:48 p.m. |
| NEDg | Description generation | batch_69f62c7b28588190839c35c19856d16f |
completed | May 2, 2026, 4:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f62e403a308190a2bba3fefc420932 |
completed | May 2, 2026, 5:02 p.m. |
Created at: April 8, 2026, 9:54 p.m.