Triple
T18297295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Lowry |
E438263
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Lowry |
—
|
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: Lowry | Statement: [Mark Lowry, familyName, Lowry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lowry Context triple: [Mark Lowry, familyName, Lowry]
-
A.
Lowry
chosen
Lowry is a renowned English surname most famously associated with L. S. Lowry, the 20th-century painter known for his industrial landscapes and "matchstick men."
-
B.
Lawrie
Lawrie is the middle name of Wilfred Lawrie Nicholas Johnson, the son of former UK Prime Minister Boris Johnson and Carrie Johnson.
-
C.
Daughtrey
Daughtrey is a surname most notably associated with Martha Craig Daughtrey, an American judge who served on the U.S. Court of Appeals for the Sixth Circuit.
-
D.
Lorens
Lorens is a character from Paulo Coelho’s novel "Brida," serving as one of the key figures in the protagonist’s spiritual and personal journey.
-
E.
Holdaway
Holdaway is a character in Quentin Tarantino's film "Reservoir Dogs," serving as the police handler who recruits the undercover cop known as Mr. Orange.
- 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_69d8b915e3e881909125d760c15d0c29 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e5017cc540819096c103a2c72315e6 |
completed | April 19, 2026, 4:23 p.m. |
Created at: April 10, 2026, 10:35 a.m.