Triple
T19056694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexis Smith |
E466413
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Craig Stevens |
—
|
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: Craig Stevens | Statement: [Alexis Smith, spouse, Craig Stevens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Craig Stevens Context triple: [Alexis Smith, spouse, Craig Stevens]
-
A.
Craig Stevens
chosen
Craig Stevens was an American actor best known for his starring role as private detective Peter Gunn in the late-1950s television series of the same name.
-
B.
Mike Stevens
Mike Stevens is a music producer known for his work on the project "Nostalgia."
-
C.
Mark Stevens
Mark Stevens is a music producer known for his work with the artist Chaka.
-
D.
Mark Stevens
Mark Stevens was an American film and television actor best known for his roles in 1940s and 1950s dramas and film noir.
-
E.
Mark Stevens
Mark Stevens is a film editor known for his work on the thriller "Phone Booth."
- 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_69d8dd040fb881909af2a964f65ad208 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5dc067f788190b3b149dfee370435 |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 10, 2026, 12:03 p.m.