Triple
T23161130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meredith Brown |
E578586
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object | Enid Bagnold |
—
|
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: Enid Bagnold | Statement: [Meredith Brown, creator, Enid Bagnold]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Enid Bagnold Context triple: [Meredith Brown, creator, Enid Bagnold]
-
A.
Enid Bagnold
chosen
Enid Bagnold was a British novelist and playwright best known for her classic 1935 children’s novel "National Velvet."
-
B.
Millicent Bagnold
Millicent Bagnold is a former British Minister for Magic in the Harry Potter universe, best known for overseeing the wizarding world during Voldemort’s first downfall.
-
C.
Dorothy Jennings
Dorothy Jennings is a recurring character on the television series "Dr. Quinn, Medicine Woman," known as the outspoken, independent editor of the town newspaper in Colorado Springs.
-
D.
Dilys Thomas
Dilys Thomas was the mother of British broadcaster and historian Jonathan Dimbleby.
-
E.
Dorothy Whipple
Dorothy Whipple was a 20th-century English novelist known for her perceptive, character-driven domestic fiction and her popularity with middlebrow readers.
- 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_69e245fc75348190a0288401044c8af8 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f006930819097aafef87405d737 |
completed | April 29, 2026, 4:54 a.m. |
Created at: April 17, 2026, 4:02 p.m.