Triple
T3051105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | True Grit (2010 film) |
E83572
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
LaBoeuf
LaBoeuf is a Texas Ranger character in the 2010 Western film "True Grit," known for his prideful demeanor and uneasy partnership with U.S. Marshal Rooster Cogburn and young Mattie Ross.
|
E322220
|
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: LaBoeuf | Statement: [True Grit (2010 film), character, LaBoeuf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LaBoeuf Context triple: [True Grit (2010 film), character, LaBoeuf]
-
A.
Landry
Landry is a surname most famously associated with Tom Landry, the legendary longtime head coach of the Dallas Cowboys in the National Football League.
-
B.
Roscoe
"Roscoe" is an essay by Washington Irving, included in his collection *The Sketch Book of Geoffrey Crayon, Gent.*, that reflects on the life and character of English historian and writer William Roscoe.
-
C.
Milhous
Milhous is the distinctive middle name of Richard Nixon, the 37th president of the United States.
-
D.
Lamon
Lamon is an archaeological site notable for inscriptions in the ancient Venetic language.
-
E.
Ebersole
Ebersole is a surname most notably associated with American actress and singer Christine Ebersole.
- 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: LaBoeuf Triple: [True Grit (2010 film), character, LaBoeuf]
Generated description
LaBoeuf is a Texas Ranger character in the 2010 Western film "True Grit," known for his prideful demeanor and uneasy partnership with U.S. Marshal Rooster Cogburn and young Mattie Ross.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: LaBoeuf Target entity description: LaBoeuf is a Texas Ranger character in the 2010 Western film "True Grit," known for his prideful demeanor and uneasy partnership with U.S. Marshal Rooster Cogburn and young Mattie Ross.
-
A.
Landry
Landry is a surname most famously associated with Tom Landry, the legendary longtime head coach of the Dallas Cowboys in the National Football League.
-
B.
Roscoe
"Roscoe" is an essay by Washington Irving, included in his collection *The Sketch Book of Geoffrey Crayon, Gent.*, that reflects on the life and character of English historian and writer William Roscoe.
-
C.
Milhous
Milhous is the distinctive middle name of Richard Nixon, the 37th president of the United States.
-
D.
Lamon
Lamon is an archaeological site notable for inscriptions in the ancient Venetic language.
-
E.
Ebersole
Ebersole is a surname most notably associated with American actress and singer Christine Ebersole.
- 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_69ad8b24924c8190a9bb6f61d519e4ae |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9bb1a46081908547a2f27cbf3446 |
completed | March 8, 2026, 3:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1eefa84f08190a178cc0674d8a3ab |
completed | March 11, 2026, 10:38 p.m. |
| NEDg | Description generation | batch_69b1ef69d49c81908caa41a80718896b |
completed | March 11, 2026, 10:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b1f05e44e08190be8b194938b6c1c7 |
completed | March 11, 2026, 10:44 p.m. |
Created at: March 8, 2026, 3:01 p.m.