Triple
T22025872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skipper Worse |
E543960
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Sara |
—
|
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: Sara | Statement: [Skipper Worse, hasCharacter, Sara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sara Context triple: [Skipper Worse, hasCharacter, Sara]
-
A.
Sara
"Sara" is a soft rock song by Fleetwood Mac, written and sung by Stevie Nicks, known for its dreamy lyrics and prominent place on their 1979 album *Tusk*.
-
B.
Sara
chosen
Sara is the imaginative and resilient young heroine of Frances Hodgson Burnett’s classic children’s novel "A Little Princess."
-
C.
Sara
Sara is the central protagonist of the film "Runaway Train," around whom the story’s dramatic events and emotional stakes revolve.
-
D.
Sara
Sara is the central female protagonist of the Italian film "L’uomo che ama," around whom the story’s emotional and relational conflicts revolve.
-
E.
Sara
Sara is the first name of Sara Blakely, the American entrepreneur and founder of the shapewear company Spanx.
- 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_69e11e2e8ea4819084210fe06d3a1b8d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127cba61c8190a48ec2c1ee1315b0 |
completed | April 28, 2026, 9:34 p.m. |
Created at: April 16, 2026, 8:24 p.m.