Triple
T14235145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Son in Law |
E352857
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Cindy Pickett |
E680540
|
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: Cindy Pickett | Statement: [Son in Law, starring, Cindy Pickett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cindy Pickett Context triple: [Son in Law, starring, Cindy Pickett]
-
A.
Cindy Pickett
chosen
Cindy Pickett is an American actress best known for her role as Ferris Bueller’s mother in the classic 1986 teen comedy film "Ferris Bueller’s Day Off."
-
B.
Cindy Holland
Cindy Holland is a television executive best known for her influential role in developing and overseeing original content at Netflix.
-
C.
Cindy Henderson
Cindy Henderson is an actress best known for voicing Wednesday Addams in the 1970s animated adaptation of The Addams Family.
-
D.
Cindy Marcus
Cindy Marcus is a screenwriter best known for co-writing Disney's animated sequel "The Lion King II: Simba’s Pride."
-
E.
Jennifer Cossitt
Jennifer Cossitt is a Canadian politician who has served as the elected representative for the Leeds—Grenville electoral district.
- 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_69d8278adc7c8190a9218d69bce3c4e6 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de62411c888190a154acd56fe3fcaf |
completed | April 14, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffe46175b88190ae687073ddaa3d22 |
completed | May 10, 2026, 1:50 a.m. |
Created at: April 10, 2026, 1:07 a.m.