Triple
T10255380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Willard Huyck |
E240448
|
entity |
| Predicate | wroteScreenplayFor |
P15305
|
FINISHED |
| Object | Lucky Lady |
E318382
|
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: Lucky Lady | Statement: [Willard Huyck, wroteScreenplayFor, Lucky Lady]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lucky Lady Context triple: [Willard Huyck, wroteScreenplayFor, Lucky Lady]
-
A.
Lucky Lady
chosen
Lucky Lady is a 1975 American caper comedy film set during Prohibition, starring Gene Hackman, Liza Minnelli, and Burt Reynolds as rum-runners in Mexico.
-
B.
Lucky Lady II
Lucky Lady II was a United States Air Force B-50 Superfortress famous for completing the first nonstop around-the-world flight in 1949.
-
C.
Lucky
Lucky is a regional supermarket chain brand in the United States known for its neighborhood grocery stores and value-focused offerings.
-
D.
Lucky
Lucky is the nickname of John "Lucky" Garnett, likely highlighting a reputation for good fortune or narrow escapes.
-
E.
Lucky
Lucky is a recurring dog character in the animated children's series "Bluey," known as Bluey's sporty next-door neighbor and friend.
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d24c69ac81908b4da53d13407ac8 |
completed | April 7, 2026, 9:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71cd263748190b02540b007c5453d |
completed | April 9, 2026, 3:28 a.m. |
Created at: April 6, 2026, 11:30 a.m.