Triple
T20245430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Cho |
E498412
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
John
John is the given name of actor John Cho, a Korean American performer known for roles in the "Harold & Kumar" films and the "Star Trek" reboot series.
|
E498412
|
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: John | Statement: [John Cho, givenName, John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Context triple: [John Cho, givenName, John]
-
A.
John
John is the given first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
-
B.
John
John is the given first name of the 19th-century English theologian and social reformer Frederick Denison Maurice.
-
C.
John
John is the given name of John Eales, the renowned former Australian rugby union captain and World Cup winner.
-
D.
John
John is the given first name of the American Old West outlaw and gunfighter Johnny Ringo.
-
E.
John
John is the given name of American novelist and historical fiction writer John Jakes, best known for his sprawling family sagas set during pivotal periods of U.S. history.
- 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: John Triple: [John Cho, givenName, John]
Generated description
John is the given name of actor John Cho, a Korean American performer known for roles in the "Harold & Kumar" films and the "Star Trek" reboot series.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Target entity description: John is the given name of actor John Cho, a Korean American performer known for roles in the "Harold & Kumar" films and the "Star Trek" reboot series.
-
A.
John
chosen
John is the given name of actor John Cho, a Korean American performer known for roles in the "Harold & Kumar" films and the "Star Trek" reboot series.
-
B.
John
John is the given name of American actor John Goodman, renowned for his roles in film, television, and theater.
-
C.
John
John is the given name of John Witherspoon, an American actor and comedian best known for his roles in the "Friday" film series and the television show "The Wayans Bros."
-
D.
John
John is the given name of American actor John Phillip Law, known for his roles in films such as "Barbarella" and "The Golden Voyage of Sinbad."
-
E.
John
John is the given name of British actor and producer John Boyega, known for his role as Finn in the Star Wars sequel trilogy.
- 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_69da6274c58c81909c646eabed6f4f30 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e673a26c8481908f408fb6426aece9 |
completed | April 20, 2026, 6:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0855222ac88190b8e950fcc12418e7 |
completed | May 16, 2026, 11:29 a.m. |
| NEDg | Description generation | batch_6a0855d7d87481908ff14d53a2ac94f7 |
completed | May 16, 2026, 11:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0856da3e748190866c328a6c61b3d8 |
completed | May 16, 2026, 11:36 a.m. |
Created at: April 11, 2026, 11:40 p.m.