Triple
T15596471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raby |
E374904
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Mark Raby
Mark Raby is a technology and gaming journalist known for his coverage of video games, consumer electronics, and digital culture.
|
E1171759
|
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: Mark Raby | Statement: [Raby, hasNotableBearer, Mark Raby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Raby Context triple: [Raby, hasNotableBearer, Mark Raby]
-
A.
James Raby
James Raby is an individual notable enough to be recognized as a prominent bearer of the surname Raby.
-
B.
Peter Raby
Peter Raby is a British biographer and literary scholar best known for his works on figures such as Oscar Wilde and Alfred Russel Wallace.
-
C.
Martin Rabbett
Martin Rabbett is an American actor and producer best known for his long-term personal and professional partnership with actor Richard Chamberlain.
-
D.
Jonathan Brackley
Jonathan Brackley is a British television writer and producer best known for co-creating and writing the sci-fi drama series "Humans."
-
E.
Martin Bladen
Martin Bladen was an 18th-century British politician and colonial administrator whose influence in imperial affairs led to places such as Bladen County, North Carolina being named in his honor.
- 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: Mark Raby Triple: [Raby, hasNotableBearer, Mark Raby]
Generated description
Mark Raby is a technology and gaming journalist known for his coverage of video games, consumer electronics, and digital culture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mark Raby Target entity description: Mark Raby is a technology and gaming journalist known for his coverage of video games, consumer electronics, and digital culture.
-
A.
James Raby
James Raby is an individual notable enough to be recognized as a prominent bearer of the surname Raby.
-
B.
Peter Raby
Peter Raby is a British biographer and literary scholar best known for his works on figures such as Oscar Wilde and Alfred Russel Wallace.
-
C.
Martin Rabbett
Martin Rabbett is an American actor and producer best known for his long-term personal and professional partnership with actor Richard Chamberlain.
-
D.
Jonathan Brackley
Jonathan Brackley is a British television writer and producer best known for co-creating and writing the sci-fi drama series "Humans."
-
E.
Martin Bladen
Martin Bladen was an 18th-century British politician and colonial administrator whose influence in imperial affairs led to places such as Bladen County, North Carolina being named in his honor.
- 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_69d85cce25008190b13b52745fbd719b |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e5f9db8819083abf80f01f32b3d |
completed | April 16, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff75655c948190aa1afa424e5270d1 |
completed | May 9, 2026, 5:56 p.m. |
| NEDg | Description generation | batch_69ff761a18e4819089a4a722884ded9c |
completed | May 9, 2026, 5:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff76c0f9c48190aff58b147c1ed12b |
completed | May 9, 2026, 6:02 p.m. |
Created at: April 10, 2026, 4:12 a.m.