Triple
T17493694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sir Matthew Lamb, 1st Baronet |
E425994
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Matthew
Matthew is the given name of Sir Matthew Lamb, 1st Baronet, an 18th-century British politician and landowner.
|
E1271595
|
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: [Sir Matthew Lamb, 1st Baronet, givenName, Matthew]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matthew Context triple: [Sir Matthew Lamb, 1st Baronet, 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 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 Bowen, a British novelist and playwright known for his crime and speculative fiction.
-
E.
John
John is the given name of Sir John Lennard-Jones, a pioneering British theoretical chemist known for his work on intermolecular forces and the Lennard-Jones potential.
- 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: [Sir Matthew Lamb, 1st Baronet, givenName, Matthew]
Generated description
Matthew is the given name of Sir Matthew Lamb, 1st Baronet, an 18th-century British politician and landowner.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Matthew Target entity description: Matthew is the given name of Sir Matthew Lamb, 1st Baronet, an 18th-century British politician and landowner.
-
A.
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.
-
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 given name of the pioneering British Egyptologist and archaeologist Flinders Petrie, renowned for developing systematic excavation and seriation methods.
-
D.
Matthew
Matthew is the middle name of Sir James Matthew Barrie, the Scottish novelist and playwright best known as the creator of Peter Pan.
-
E.
Matthew
Matthew is the full given name of American television journalist and former "Today" show co-host Matt Lauer.
- 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_69d889dccf7481909264a1844a2e9100 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451d782688190afb76fa080867315 |
completed | April 19, 2026, 3:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01c202b7c48190bb2d58a77c8eca80 |
completed | May 11, 2026, 11:48 a.m. |
| NEDg | Description generation | batch_6a01c2aa19408190840547b60786cc18 |
completed | May 11, 2026, 11:51 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01c35d05388190ade7044202781e20 |
completed | May 11, 2026, 11:54 a.m. |
Created at: April 10, 2026, 5:48 a.m.