Triple
T7782215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wendy Lawrence |
E221547
|
entity |
| Predicate | fullName |
P16
|
FINISHED |
| Object | Wendy Barrien Lawrence |
E221547
|
NE FINISHED |
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: Wendy Barrien Lawrence | Statement: [Wendy Lawrence, fullName, Wendy Barrien Lawrence]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wendy Barrien Lawrence Context triple: [Wendy Lawrence, fullName, Wendy Barrien Lawrence]
-
A.
Wendy Lawrence
chosen
Wendy Lawrence is a retired U.S. Navy captain and NASA astronaut who flew on multiple Space Shuttle missions as a mission specialist.
-
B.
Marlene Lawston
Marlene Lawston is an American actress best known for her role as Jodie Foster’s daughter in the thriller film "Flightplan."
-
C.
Ann Lawlor
Ann Lawlor is a Canadian municipal politician who serves as the mayor of Halton Hills, Ontario.
-
D.
Linda Banwell
Linda Banwell is best known as the wife of the late English actor and director Bob Hoskins.
-
E.
Wendy Hughes
Wendy Hughes was an acclaimed Australian actress known for her versatile performances in film, television, and theatre from the 1970s onward.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca83ebbef881909ac47f789145fef7 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cadf1dcc6c8190b3c6ee4ff7808e02 |
completed | March 30, 2026, 8:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69caf5d30c748190bbb71534cfdf4f75 |
completed | March 30, 2026, 10:14 p.m. |
Created at: March 30, 2026, 4:21 p.m.