Triple
T22880784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freddie Dalton Thompson |
E567459
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Sarah Lindsey Baker |
—
|
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: Sarah Lindsey Baker | Statement: [Freddie Dalton Thompson, spouse, Sarah Lindsey Baker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarah Lindsey Baker Context triple: [Freddie Dalton Thompson, spouse, Sarah Lindsey Baker]
-
A.
Sarah Lindsey Baker
chosen
Sarah Lindsey Baker is best known as the wife of the late American actor, lawyer, and U.S. Senator Fred Thompson.
-
B.
Rebecca Baker
Rebecca Baker is known as the daughter of acclaimed special effects makeup artist and film industry figure Rick Baker.
-
C.
Anne Baker
Anne Baker is a political leader who serves as the mayor of the Isaac Region.
-
D.
Rose Baker
Rose Baker is a student who receives academic tutoring from Megan Smith.
-
E.
Rose Baker
Rose Baker is a fictional character typically portrayed as a young woman from a wealthy, socially advantaged background.
- 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_69e2458a92ec81908fc1cd5f6407d2ab |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17f5c1ed88190aeac131c5aff6102 |
completed | April 29, 2026, 3:47 a.m. |
Created at: April 17, 2026, 3:39 p.m.