Triple
T9105792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Randolph Scott |
E218474
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
George
George is the given first name of American film actor Randolph Scott, known for his roles in classic Western movies.
|
E777167
|
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: [Randolph Scott, givenName, George]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: George Context triple: [Randolph Scott, givenName, George]
-
A.
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.
-
B.
George
George is the birth name of the legendary American baseball player Babe Ruth, one of the sport’s most iconic figures.
-
C.
George
George is a masculine given name of Greek origin meaning "farmer" or "earthworker," widely used in English-speaking and many other cultures.
-
D.
George
George is the given name of the Hero of Manila Bay, most famously associated with U.S. Admiral George Dewey, who led the decisive naval victory at the Battle of Manila Bay during the Spanish–American War.
-
E.
George
George is the given name of George Carnegie, 6th Earl of Northesk, a Scottish nobleman and naval officer in the Royal Navy.
- 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: [Randolph Scott, givenName, George]
Generated description
George is the given first name of American film actor Randolph Scott, known for his roles in classic Western movies.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: George Target entity description: George is the given first name of American film actor Randolph Scott, known for his roles in classic Western movies.
-
A.
George
George is the given name of American actor George Peppard, best known for starring in the television series "The A-Team" and films such as "Breakfast at Tiffany's."
-
B.
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.
-
C.
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.
-
D.
George
George is the given name of George Armstrong Custer, the controversial U.S. Army officer and cavalry commander best known for his defeat and death at the Battle of the Little Bighorn.
-
E.
George
George is the given name of George W. Norris, a prominent early 20th-century American politician known for his progressive reforms and long service in the U.S. Congress.
- 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_69ca83db7448819090d0a5de842ef2ac |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca57286a88190b256d2461c5c0aed |
completed | April 1, 2026, 4:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d01840d2488190a14d458aa181cc47 |
completed | April 3, 2026, 7:42 p.m. |
| NEDg | Description generation | batch_69d0196766248190aebda80cbd7d1eef |
completed | April 3, 2026, 7:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d019d76d2481909118b163ce5713f2 |
completed | April 3, 2026, 7:49 p.m. |
Created at: March 30, 2026, 7:16 p.m.