Triple
T17198933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarah Porter |
E417425
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Sarah Porter |
E417425
|
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: Sarah Porter | Statement: [Sarah Porter, name, Sarah Porter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarah Porter Context triple: [Sarah Porter, name, Sarah Porter]
-
A.
Sarah Porter
chosen
Sarah Porter was a 19th-century American educator best known for founding Miss Porter’s School, an elite college-preparatory school for girls in Farmington, Connecticut.
-
B.
Caitlin Blackwood
Caitlin Blackwood is a Scottish actress best known for playing the young Amelia Pond in the BBC science fiction series Doctor Who.
-
C.
Oaklee Pendergast
Oaklee Pendergast is a British child actor best known for his role in the disaster drama film "The Impossible."
-
D.
Kate Flax
Kate Flax is the teenage daughter of an eccentric single mother in the film "Mermaids," navigating adolescence, identity, and family turmoil in 1960s New England.
-
E.
Miranda Greene
Miranda Greene is a fictional character from the comedy film "King Ralph," where she serves as a key romantic interest and supporting figure in the story of an unlikely American who becomes the King of England.
- 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_69d886d6ba8c819093215917b3d01689 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42daca29081909837494d8d516634 |
completed | April 19, 2026, 1:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a015fd7ef048190b0828ec6ea0e119c |
completed | May 11, 2026, 4:49 a.m. |
Created at: April 10, 2026, 5:38 a.m.