Triple
T19727647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Satiromastix |
E473767
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object |
Sir Vaughan
Sir Vaughan is a character in Thomas Dekker’s early 17th-century satirical play "Satiromastix," which lampoons contemporary literary figures and theatrical rivalries.
|
E1392896
|
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: Sir Vaughan | Statement: [Satiromastix, featuresCharacter, Sir Vaughan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sir Vaughan Context triple: [Satiromastix, featuresCharacter, Sir Vaughan]
-
A.
Hugh Williams
Hugh Williams was a British actor and playwright known for his work in mid-20th-century film, theatre, and television.
-
B.
Hugh Vaughan
Hugh Vaughan is an actor known for his role in the British film "The Englishman Who Went Up a Hill But Came Down a Mountain."
-
C.
Will Rees
Will Rees is a British musician best known as a guitarist and member of the indie rock band Mystery Jets.
-
D.
Emrys Jones
Emrys Jones was a distinguished British geographer recognized for his influential work in urban and social geography.
-
E.
Simon Vaughan
Simon Vaughan is the conflicted, battle-hardened gunrunner protagonist of Jack Higgins’ novel "The Savage Day," drawn back into violence during the Northern Ireland Troubles.
- 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: Sir Vaughan Triple: [Satiromastix, featuresCharacter, Sir Vaughan]
Generated description
Sir Vaughan is a character in Thomas Dekker’s early 17th-century satirical play "Satiromastix," which lampoons contemporary literary figures and theatrical rivalries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sir Vaughan Target entity description: Sir Vaughan is a character in Thomas Dekker’s early 17th-century satirical play "Satiromastix," which lampoons contemporary literary figures and theatrical rivalries.
-
A.
Hugh Williams
Hugh Williams was a British actor and playwright known for his work in mid-20th-century film, theatre, and television.
-
B.
Hugh Vaughan
Hugh Vaughan is an actor known for his role in the British film "The Englishman Who Went Up a Hill But Came Down a Mountain."
-
C.
Will Rees
Will Rees is a British musician best known as a guitarist and member of the indie rock band Mystery Jets.
-
D.
Emrys Jones
Emrys Jones was a distinguished British geographer recognized for his influential work in urban and social geography.
-
E.
Simon Vaughan
Simon Vaughan is the conflicted, battle-hardened gunrunner protagonist of Jack Higgins’ novel "The Savage Day," drawn back into violence during the Northern Ireland Troubles.
- 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_69d8e517ebd48190979ee76723bcfadf |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e649fa1bc481908a9e7cf4fc52f75c |
completed | April 20, 2026, 3:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07b4f0728881909ccadf9e738e371c |
completed | May 16, 2026, 12:06 a.m. |
| NEDg | Description generation | batch_6a07b5e9961881908f224154ec12c366 |
completed | May 16, 2026, 12:10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07b67964b481909af269c6b5db6527 |
completed | May 16, 2026, 12:12 a.m. |
Created at: April 10, 2026, 1:47 p.m.