Triple
T21413435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Professional Soldier |
E528235
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Gloria Stuart |
—
|
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: Gloria Stuart | Statement: [Professional Soldier, starring, Gloria Stuart]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gloria Stuart Context triple: [Professional Soldier, starring, Gloria Stuart]
-
A.
Gloria Stuart
chosen
Gloria Stuart was an American actress best known for her Oscar-nominated role as the elderly Rose in James Cameron’s film "Titanic."
-
B.
Jessica Tandy
Jessica Tandy was an acclaimed British-American actress known for her distinguished stage and film career, including her Academy Award–winning performance in "Driving Miss Daisy."
-
C.
Mary Gish
Mary Gish was the mother of famed silent film actresses Lillian and Dorothy Gish, known for supporting their early careers in the motion picture industry.
-
D.
Thelma Ritter
Thelma Ritter was an acclaimed American character actress known for her sharp-tongued, humorous supporting roles in classic mid-20th-century films and for receiving multiple Academy Award nominations.
-
E.
Shirley Heath
Shirley Heath is a large open heathland and recreational green space located in the Shirley area of the West Midlands, England.
- 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_69e0c454c248819093425d1099101c09 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e8b201ce1481908392c77e5ca40f5f |
completed | April 22, 2026, 11:33 a.m. |
Created at: April 16, 2026, 5:44 p.m.