Triple
T2480901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ron Howard |
E55811
|
entity |
| Predicate | parentOf |
P120
|
FINISHED |
| Object | Paige Howard |
E42855
|
NE FINISHED |
How this triple was built (2 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: Paige Howard | Statement: [Ron Howard, parentOf, Paige Howard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paige Howard Context triple: [Ron Howard, parentOf, Paige Howard]
-
A.
Paige Howard
chosen
Paige Howard is an American actress known for her work in film, television, and theater, and as a member of the Howard entertainment family.
-
B.
Paige Hurd
Paige Hurd is an American actress best known for her roles in television series such as "Everybody Hates Chris" and "The Oval," as well as various film appearances.
-
C.
Paige Alexander
Paige Alexander is an American nonprofit leader and former U.S. government official who serves as the chief executive officer of The Carter Center.
-
D.
Paige Butcher
Paige Butcher is an Australian model and actress known for her work in film and fashion, as well as her long-term relationship with comedian and actor Eddie Murphy.
-
E.
Lacey Pemberton
Lacey Pemberton is a popular high school girl and one of the central characters in John Green’s novel and film adaptation "Paper Towns."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ab49e670a88190b928e08302381710 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd161bf3c8190834502968180e9cf |
completed | March 7, 2026, 7:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af17b146d881909672e9cd4a501a11 |
completed | March 9, 2026, 6:55 p.m. |
Created at: March 6, 2026, 9:45 p.m.