Triple
T12875437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matthew Salinger |
E307953
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Matthew
Matthew is a masculine given name of Hebrew origin meaning "gift of God," widely used in English-speaking and many other cultures.
|
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 Salinger, givenName, Matthew]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matthew Context triple: [Matthew Salinger, 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 McDowell is a prominent South African-born philosopher known for his influential work in epistemology, philosophy of mind, and ethics.
-
E.
John
John Cicero was a late 15th-century Elector of Brandenburg from the House of Hohenzollern who helped consolidate the territory’s political and administrative structures within the Holy Roman Empire.
- 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 Salinger, givenName, Matthew]
Generated description
Matthew is a masculine given name of Hebrew origin meaning "gift of God," widely used in English-speaking and many other cultures.
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 meaning "gift of God," widely used in English-speaking and many other cultures.
-
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 given name of the pioneering British Egyptologist and archaeologist Flinders Petrie, renowned for developing systematic excavation and seriation methods.
-
D.
Matthew
Matthew is the full given name of American former professional stock car racing driver Matt Kenseth, a NASCAR Cup Series champion.
-
E.
Matthew
Matthew is the full given name of American television journalist and former "Today" show co-host Matt Lauer.
- 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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d970f97f9c81908c75259a4cab1d3c |
completed | April 10, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69bb679f88190a1799b73c3f738b6 |
completed | May 3, 2026, 12:49 a.m. |
| NEDg | Description generation | batch_69f69fb238f08190a0c63d71bfbe4529 |
completed | May 3, 2026, 1:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6a087120c81908644ed732eff4d99 |
completed | May 3, 2026, 1:10 a.m. |
Created at: April 9, 2026, 5:38 p.m.