Triple
T5365980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lord Goring |
E103131
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
George
George is the given name of Lord Goring, a witty and fashionable character in Oscar Wilde’s play "An Ideal Husband."
|
E514862
|
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: George | Statement: [Lord Goring, givenName, George]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: George Context triple: [Lord Goring, givenName, George]
-
A.
George
George is the first name of George Washington, the first President of the United States and a key leader in the American Revolutionary War.
-
B.
George
George is the heroic protagonist of the fantasy film "The Magic Sword," known for embarking on a perilous quest to rescue a princess from an evil sorcerer.
-
C.
George
George is one of the central child detectives in Enid Blyton’s classic Secret Seven mystery series.
-
D.
George
George is the given name of George Washington Vanderbilt II, the American art collector and member of the prominent Vanderbilt family who built the Biltmore Estate.
-
E.
George
George is the birth name of the legendary American baseball player Babe Ruth, one of the sport’s most iconic figures.
- 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: George Triple: [Lord Goring, givenName, George]
Generated description
George is the given name of Lord Goring, a witty and fashionable character in Oscar Wilde’s play "An Ideal Husband."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: George Target entity description: George is the given name of Lord Goring, a witty and fashionable character in Oscar Wilde’s play "An Ideal Husband."
-
A.
George
George is the given first name of the fictional character Gob Bluth from the television series "Arrested Development."
-
B.
George
George is the given name of George Bellas Greenough, a pioneering 19th-century English geologist and founding figure of the Geological Society of London.
-
C.
George
George is a male given name commonly used in English-speaking countries and borne by numerous historical figures, including kings, presidents, and cultural icons.
-
D.
George
George is a middle-aged, embittered history professor whose caustic wit and psychological games drive the intense marital drama in Edward Albee’s play "Who’s Afraid of Virginia Woolf?".
-
E.
George
George is the given name of George Stanley, 9th Baron Strange, an English nobleman and politician of the late 15th century.
- 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_69bd43daa3e4819090b59d127db70e57 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd8682d18c8190bbb35cc75c8a7c12 |
completed | March 20, 2026, 5:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf291610b4819086e04f232e4eba7d |
completed | March 21, 2026, 11:26 p.m. |
| NEDg | Description generation | batch_69bf2996154c81909bd5aca5cdc4e426 |
completed | March 21, 2026, 11:28 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf29f6a5b0819096e53ce3a7e14266 |
completed | March 21, 2026, 11:29 p.m. |
Created at: March 20, 2026, 2:02 p.m.