Triple
T18783544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morgan |
E459318
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Morgans |
—
|
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: Morgans | Statement: [Morgan, hasVariant, Morgans]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Morgans Context triple: [Morgan, hasVariant, Morgans]
-
A.
Morgans
chosen
Morgans is a Welsh surname borne by various notable individuals, including figures in sports, politics, and the arts.
-
B.
Bassett
Bassett is the surname of acclaimed American actress and director Angela Bassett, known for her powerful performances in film and television.
-
C.
Bassett
Bassett is the young gardener and betting partner in D. H. Lawrence’s short story “The Rocking-Horse Winner,” who helps the protagonist place successful horse-race wagers.
-
D.
Shires
Shires is the surname of American singer-songwriter and fiddle player Amanda Shires, known for her solo work and collaborations in Americana and country music.
-
E.
Sidney Morgan
Sidney Morgan is an actor known for appearing in the film adaptation of Sean O'Casey’s play "Juno and the Paycock."
- 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_69d8d396f54c8190ba49db31e8743842 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5977f34e48190a9932af330ea4f92 |
completed | April 20, 2026, 3:03 a.m. |
Created at: April 10, 2026, 11:52 a.m.