Triple
T6150565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McFarland, USA |
E137188
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Johnny Ortiz
Johnny Ortiz is an American actor best known for his role in the inspirational sports drama film "McFarland, USA."
|
E571139
|
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: Johnny Ortiz | Statement: [McFarland, USA, starring, Johnny Ortiz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Johnny Ortiz Context triple: [McFarland, USA, starring, Johnny Ortiz]
-
A.
Mickey McGuire
Mickey McGuire is the early screen persona of American actor Mickey Rooney, used in a popular series of comedy short films in the late 1920s and early 1930s.
-
B.
Jack Oaker
Jack Oaker was the husband of silent film actress Belle Bennett, known primarily in relation to her life and career.
-
C.
Don Altobello
Don Altobello is an elderly, seemingly benevolent but ultimately treacherous Mafia don who plays a key antagonist role in the crime drama film "The Godfather Part III."
-
D.
Todd Casey
Todd Casey is a screenwriter best known for co-writing the 2015 horror-comedy film "Krampus."
-
E.
Mickey O'Neil
Mickey O'Neil is a fast-talking, bare-knuckle boxing Irish Traveller and pivotal figure in the British crime film "Snatch," known for his unpredictable nature and thick accent.
- 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: Johnny Ortiz Triple: [McFarland, USA, starring, Johnny Ortiz]
Generated description
Johnny Ortiz is an American actor best known for his role in the inspirational sports drama film "McFarland, USA."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Johnny Ortiz Target entity description: Johnny Ortiz is an American actor best known for his role in the inspirational sports drama film "McFarland, USA."
-
A.
Mickey McGuire
Mickey McGuire is the early screen persona of American actor Mickey Rooney, used in a popular series of comedy short films in the late 1920s and early 1930s.
-
B.
Jack Oaker
Jack Oaker was the husband of silent film actress Belle Bennett, known primarily in relation to her life and career.
-
C.
Don Altobello
Don Altobello is an elderly, seemingly benevolent but ultimately treacherous Mafia don who plays a key antagonist role in the crime drama film "The Godfather Part III."
-
D.
Todd Casey
Todd Casey is a screenwriter best known for co-writing the 2015 horror-comedy film "Krampus."
-
E.
Mickey O'Neil
Mickey O'Neil is a fast-talking, bare-knuckle boxing Irish Traveller and pivotal figure in the British crime film "Snatch," known for his unpredictable nature and thick accent.
- 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_69c008a45d008190832a9e19f5d63406 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05ce329648190a03ba0233df841fa |
completed | March 22, 2026, 9:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1360d84e081909ff6c06e3bd54aee |
completed | March 23, 2026, 12:46 p.m. |
| NEDg | Description generation | batch_69c137d902c08190a857814ff70a82eb |
completed | March 23, 2026, 12:53 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c1389690e88190b1a9045c3a8fc892 |
completed | March 23, 2026, 12:56 p.m. |
Created at: March 22, 2026, 4:16 p.m.