Triple
T20541964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laura Wright |
E504361
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Wright |
—
|
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: Wright | Statement: [Laura Wright, familyName, Wright]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wright Context triple: [Laura Wright, familyName, Wright]
-
A.
Wright
chosen
Wright is a common English surname borne by numerous notable individuals across politics, sports, arts, and science.
-
B.
Wright
Wright is the surname of Tré Cool, the German-born American drummer best known for his work with the punk rock band Green Day.
-
C.
Wright
Wright is an Australian federal electoral division in Queensland represented in the House of Representatives.
-
D.
Wright-Martin
Wright-Martin was an early 20th-century American aircraft engine and aviation company known for producing licensed versions of European aero engines during World War I.
-
E.
Wright Brand
Wright Brand is a bacon-focused meat brand known for its thick-cut, hardwood-smoked products, owned by Tyson Foods.
- 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_69e0b4b476648190bc6019622ae54d3c |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a292dd1c8190b5c3031f3b44eb52 |
completed | April 20, 2026, 10:02 p.m. |
Created at: April 16, 2026, 11:37 a.m.