Triple
T11396146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Make Room for Daddy |
E269977
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Sherry Jackson |
E604937
|
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: Sherry Jackson | Statement: [Make Room for Daddy, starring, Sherry Jackson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sherry Jackson Context triple: [Make Room for Daddy, starring, Sherry Jackson]
-
A.
Sherry Jackson
chosen
Sherry Jackson is an American actress best known for her work as a child and young adult performer in 1950s and 1960s film and television.
-
B.
Sherry Marsh
Sherry Marsh is a television and film producer best known for executive producing acclaimed series such as "Vikings."
-
C.
Sherry Shourds
Sherry Shourds was an American film assistant director recognized in early Hollywood, notably honored at the 7th Academy Awards.
-
D.
Sherry Nelson
Sherry Nelson is known as the former spouse of Academy Award–winning American actor Rod Steiger.
-
E.
Sherry Dyson
Sherry Dyson is an American mathematics educator best known as the former wife of entrepreneur and motivational speaker Chris Gardner, whose life inspired the film "The Pursuit of Happyness."
- 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_69d6aacdbc6c8190af6dc3d5f5d22836 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d80019d3d48190a2f473deb6eae33a |
completed | April 9, 2026, 7:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5bab66488190a465e40f1181506e |
completed | May 8, 2026, 3:42 a.m. |
Created at: April 8, 2026, 9:34 p.m.