Triple
T22969584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Kingman |
E571145
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object |
Peyton Kelly
Peyton Kelly is the young daughter of fictional NFL quarterback Joe Kingman in the family comedy film "The Game Plan."
|
E1563838
|
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: Peyton Kelly | Statement: [Joe Kingman, hasChild, Peyton Kelly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peyton Kelly Context triple: [Joe Kingman, hasChild, Peyton Kelly]
-
A.
Peyton Westlake
Peyton Westlake is a disfigured scientist-turned-vigilante who uses synthetic skin and brutal methods to seek revenge in the Darkman film series.
-
B.
Peyton Van Den Broeck
Peyton Van Den Broeck is known as the spouse of Dutch Van Den Broeck, a central character in the crime novel and film "Random Hearts."
-
C.
Peyton
Peyton is a given name most famously borne by Peyton Randolph, the first president of the Continental Congress in early American history.
-
D.
Peyton List
Peyton List is an American actress and model best known for her roles on Disney Channel series such as "Jessie" and "Bunk'd."
-
E.
Kelsey Peters
Kelsey Peters is a driven and ambitious young publishing executive and one of the central protagonists on the television series "Younger."
- 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: Peyton Kelly Triple: [Joe Kingman, hasChild, Peyton Kelly]
Generated description
Peyton Kelly is the young daughter of fictional NFL quarterback Joe Kingman in the family comedy film "The Game Plan."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Peyton Kelly Target entity description: Peyton Kelly is the young daughter of fictional NFL quarterback Joe Kingman in the family comedy film "The Game Plan."
-
A.
Peyton Westlake
Peyton Westlake is a disfigured scientist-turned-vigilante who uses synthetic skin and brutal methods to seek revenge in the Darkman film series.
-
B.
Peyton Van Den Broeck
Peyton Van Den Broeck is known as the spouse of Dutch Van Den Broeck, a central character in the crime novel and film "Random Hearts."
-
C.
Peyton
Peyton is a given name most famously borne by Peyton Randolph, the first president of the Continental Congress in early American history.
-
D.
Peyton List
Peyton List is an American actress and model best known for her roles on Disney Channel series such as "Jessie" and "Bunk'd."
-
E.
Kelsey Peters
Kelsey Peters is a driven and ambitious young publishing executive and one of the central protagonists on the television series "Younger."
- 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_69e245b2c6548190a0e4c7f2f7df2d48 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18231459881909dd25a0630c494d8 |
completed | April 29, 2026, 3:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0bca266bc08190bc202dc9b600e1fe |
completed | May 19, 2026, 2:25 a.m. |
| NEDg | Description generation | batch_6a0bcadb470c8190a402cc0792f5bcc5 |
completed | May 19, 2026, 2:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0bcb9709b48190bbc418d194fd3e07 |
completed | May 19, 2026, 2:31 a.m. |
Created at: April 17, 2026, 3:48 p.m.