Triple
T21664875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Josephine Hart |
E534687
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Hart |
—
|
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: Hart | Statement: [Josephine Hart, familyName, Hart]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hart Context triple: [Josephine Hart, familyName, Hart]
-
A.
Hart
Hart was a British racing engine manufacturer best known for supplying competitive turbo and naturally aspirated engines to various Formula One and other motorsport teams in the 1970s–1990s.
-
B.
Hart
chosen
Hart is a surname most famously associated with Moss Hart, the acclaimed American playwright and theater director known for works like "You Can't Take It with You" and "Once in a Lifetime."
-
C.
Hart
Hart is a local government district and civil parish area in Hampshire, England, known for its high quality of life and largely rural character.
-
D.
Good Hart
Good Hart is a small unincorporated community and lakeside resort area on the shore of Lake Michigan in northern Michigan.
-
E.
Hood
"Hood" is a novel by Emma Donoghue that explores grief, identity, and a lesbian relationship in contemporary Ireland.
- 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_69e0c467e1f48190af2650b19175abc4 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef6c0b26c8819092c13e59dcc3c25c |
completed | April 27, 2026, 2 p.m. |
Created at: April 16, 2026, 6:36 p.m.