Triple
T20140224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs. America |
E491143
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Michael London |
—
|
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: Michael London | Statement: [Mrs. America, executiveProducer, Michael London]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael London Context triple: [Mrs. America, executiveProducer, Michael London]
-
A.
Michael London
chosen
Michael London is a film producer known for his work on acclaimed independent movies such as "Sideways" and "Charlie Bartlett."
-
B.
Jason London
Jason London is an American actor best known for his role as high school quarterback Randall "Pink" Floyd in the cult coming-of-age film *Dazed and Confused*.
-
C.
Tony Lundon
Tony Lundon is an Irish singer and dancer best known as a member of the early-2000s British-Irish pop group Liberty X.
-
D.
Anthony Steel
Anthony Steel was a British film actor prominent in the 1950s, known for his leading-man roles in war dramas and adventure films.
-
E.
Grant Matthews
Grant Matthews is the ambitious, idealistic businessman-turned-presidential-candidate who serves as the central figure in the political drama film "State of the Union."
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e66798d59c81908ebcd6644b1b3744 |
completed | April 20, 2026, 5:51 p.m. |
Created at: April 11, 2026, 11:32 p.m.