Triple
T21447966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jordan Ladd |
E529126
|
entity |
| Predicate | workedWith |
P398
|
FINISHED |
| Object | Cheryl Ladd |
—
|
NE NERFINISHED |
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: Cheryl Ladd | Statement: [Jordan Ladd, workedWith, Cheryl Ladd]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cheryl Ladd Context triple: [Jordan Ladd, workedWith, Cheryl Ladd]
-
A.
Cheryl Ladd
chosen
Cheryl Ladd is
-
B.
Stefanie Powers
Stefanie Powers is an American actress best known for her role as Jennifer Hart in the television series "Hart to Hart."
-
C.
Lee Russo
Lee Russo is known as the spouse of American television host and film critic Ben Mankiewicz.
-
D.
Nancy Kyes
Nancy Kyes is an American actress best known for her roles in John Carpenter films, including the original Halloween and Assault on Precinct 13.
-
E.
Lesley Ann Warren
Lesley Ann Warren is an American actress and singer known for her work in film, television, and musical theater, including prominent roles in 1960s musicals and later acclaimed performances in movies and TV series.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c457579481909db68053ed99750c |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9e9d04548819086594c20faa5217d |
completed | April 23, 2026, 9:43 a.m. |
Created at: April 16, 2026, 6:06 p.m.