Triple
T21709008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sara Paxton |
E535849
|
entity |
| Predicate | performedIn |
P795
|
FINISHED |
| Object | Sydney White |
—
|
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: Sydney White | Statement: [Sara Paxton, performedIn, Sydney White]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sydney White Context triple: [Sara Paxton, performedIn, Sydney White]
-
A.
Sydney White
chosen
Sydney White is a 2007 teen romantic comedy film loosely based on the Snow White fairy tale, starring Amanda Bynes as a college freshman challenging campus social hierarchies.
-
B.
Kim White
Kim White is a cinematographer best known for her work on the animated film "Inside Out."
-
C.
Sydney Rowell
Sydney Rowell was a senior Australian Army officer and World War II general who became one of the country’s leading military commanders.
-
D.
Sydney Carroll
Sydney Carroll was a key theatrical figure known for establishing London's Regent's Park Open Air Theatre, a prominent outdoor performance venue.
-
E.
Sara White
Sara White was the wife of American novelist and journalist Theodore Dreiser.
- 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_69e0c46b44c0819088ab883ebd44e0e8 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69efb5321d34819091f3cd03f7b407c0 |
completed | April 27, 2026, 7:12 p.m. |
Created at: April 16, 2026, 6:46 p.m.