Triple
T14628856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matt Le Tissier |
E343425
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
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.
|
E1110995
|
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: [Matt Le Tissier, givenName, Matthew]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matthew Context triple: [Matt Le Tissier, givenName, Matthew]
-
A.
John
John Vassall Jr. was a British civil servant who became notorious as a Soviet spy during the Cold War.
-
B.
John
John is the given first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
-
C.
John
John is the given name of John Albert William Spencer-Churchill, a British aristocrat and 10th Duke of Marlborough.
-
D.
John
John is the given name of John Bowen, a British novelist and playwright known for his crime and speculative fiction.
-
E.
John
John is the given name of John Boyle O'Reilly, a 19th-century Irish-born poet, journalist, and civil rights activist who became influential in the United States.
- 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: [Matt Le Tissier, givenName, Matthew]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Matthew Target entity description: 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.
-
A.
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.
-
B.
Matthew
Matthew is the given name of the pioneering British Egyptologist and archaeologist Flinders Petrie, renowned for developing systematic excavation and seriation methods.
-
C.
Matthew
Matthew is a masculine given name of Hebrew origin, commonly used in English-speaking countries and meaning "gift of God."
-
D.
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.
-
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. 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_69d822dffc3c8190aa173b90761bffda |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4a7c8fc81909d10c1f563d7d1e7 |
completed | April 14, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fda92c25ac8190ba931c009e7ace19 |
completed | May 8, 2026, 9:13 a.m. |
| NEDg | Description generation | batch_69fdb7e5aa6481908d4933e3932c5d03 |
completed | May 8, 2026, 10:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fdb841f3a88190867c635950a1492c |
completed | May 8, 2026, 10:17 a.m. |
Created at: April 10, 2026, 1:26 a.m.