Triple
T22364965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matthew Dellavedova |
E552879
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Matthew
Matthew is a masculine given name of Hebrew origin, commonly used in English-speaking countries and meaning "gift of God."
|
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 Dellavedova, givenName, Matthew]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matthew Context triple: [Matthew Dellavedova, givenName, 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 Vassall Jr. was a British civil servant who became notorious as a Soviet spy during the Cold War.
-
C.
John
John is the given name of John W. Mauchly, the American physicist and co-inventor of the ENIAC computer.
-
D.
John
John is the given first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
-
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: [Matthew Dellavedova, givenName, Matthew]
Generated description
Matthew is a masculine given name of Hebrew origin, commonly used in English-speaking countries and meaning "gift of God."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Matthew Target entity description: Matthew is a masculine given name of Hebrew origin, commonly used in English-speaking countries and meaning "gift of God."
-
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 Matt Le Tissier, the renowned former Southampton and England footballer known for his exceptional skill and loyalty to a single club.
-
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 given first name of American actor Ryan Phillippe, known for films like "Cruel Intentions" and "Crash."
-
E.
Matthew
Matthew is the given name of blues guitarist Matt "Guitar" Murphy, renowned for his work with the Blues Brothers and numerous Chicago blues legends.
- 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_69e11e4affcc8190ba7c27d29062558d |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f157ffba088190ae455508eb6c2a9c |
completed | April 29, 2026, 12:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0ae065f01481909ddf2c27e2b471bf |
completed | May 18, 2026, 9:48 a.m. |
| NEDg | Description generation | batch_6a0ae16a8bcc8190852dd17f9c780123 |
completed | May 18, 2026, 9:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ae1e16fac8190b0b56d00a87d173f |
completed | May 18, 2026, 9:54 a.m. |
Created at: April 16, 2026, 8:44 p.m.