Triple
T17547221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | STS-129 |
E427359
|
entity |
| Predicate | deliveredCrewMember |
P124145
|
FINISHED |
| Object | Nicole P. Stott |
—
|
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: Nicole P. Stott | Statement: [STS-129, deliveredCrewMember, Nicole P. Stott]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nicole P. Stott Context triple: [STS-129, deliveredCrewMember, Nicole P. Stott]
-
A.
Nicole P. Stott
chosen
Nicole P. Stott is an American engineer, retired NASA astronaut, and aquanaut known for her long-duration stay on the International Space Station and her work combining space exploration with art and education.
-
B.
Alyson C. Johnson
Alyson C. Johnson is a film editor best known for her work on the 2013 thriller "The Call."
-
C.
Natalie E. Hudson
Natalie E. Hudson is an American jurist who serves as the Chief Justice of the Minnesota Supreme Court.
-
D.
Amy E. Duddleston
Amy E. Duddleston is an American film editor known for her work on major studio features and acclaimed television series.
-
E.
Christina M. Hixson
Christina M. Hixson is a philanthropist and longtime supporter of education and the arts, best known for her major charitable contributions to academic institutions.
- 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_69d889df6dc081908f67dbadc03c07ee |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e454626cfc8190a2602ba4934b8e6d |
completed | April 19, 2026, 4:04 a.m. |
Created at: April 10, 2026, 5:49 a.m.