Triple
T5907812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scoot McNairy |
E131384
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
John
John is the first name of American actor and producer Scoot McNairy, known for his roles in films like "Argo" and the series "Halt and Catch Fire."
|
E562919
|
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: [Scoot McNairy, givenName, John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Context triple: [Scoot McNairy, givenName, John]
-
A.
John
John is the given name of John H. Hammond Jr., the influential American record producer and talent scout known for discovering and promoting numerous major jazz, blues, and rock musicians.
-
B.
John
John is the given name of John F. Sattler, likely referring to him in a more informal or abbreviated context.
-
C.
John
John II of Aragon was a 15th-century King of Aragon and Navarre whose reign was marked by dynastic conflicts and the consolidation of Spanish territories.
-
D.
John
John is the given name of John B. Watson, the influential American psychologist who founded behaviorism.
-
E.
John
John is the given name of Australian cinematographer John Seale, known for his work on films such as "The English Patient" and "Mad Max: Fury Road."
- 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: [Scoot McNairy, givenName, John]
Generated description
John is the first name of American actor and producer Scoot McNairy, known for his roles in films like "Argo" and the series "Halt and Catch Fire."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Target entity description: John is the first name of American actor and producer Scoot McNairy, known for his roles in films like "Argo" and the series "Halt and Catch Fire."
-
A.
John
John is the first name of American actor Theo Rossi, known for his roles in series like "Sons of Anarchy" and "Luke Cage."
-
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 actor John Cho, a Korean American performer known for roles in the "Harold & Kumar" films and the "Star Trek" reboot series.
-
D.
John
John is the first name of American filmmaker John Lee Hancock, known for directing and writing several popular Hollywood films.
-
E.
John
John is the given name of English actor and musician John Simm, known for roles in series such as "Life on Mars" and "Doctor Who."
- 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_69c008593a44819081a07ae0efe6c574 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03772d9dc8190899fe49ef887e685 |
completed | March 22, 2026, 6:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c107ee88fc8190a6f633ff168b51ed |
completed | March 23, 2026, 9:29 a.m. |
| NEDg | Description generation | batch_69c1090a7bac8190b5b9e003659b4b34 |
completed | March 23, 2026, 9:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c10d5102348190a9ec7421b1410a99 |
completed | March 23, 2026, 9:52 a.m. |
Created at: March 22, 2026, 3:59 p.m.