Triple
T16105397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lenny |
E390725
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Stanley Beck |
E911484
|
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: Stanley Beck | Statement: [Lenny, starring, Stanley Beck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stanley Beck Context triple: [Lenny, starring, Stanley Beck]
-
A.
Stanley Beck
chosen
Stanley Beck was an American actor best known for his work in film and television during the mid-20th century.
-
B.
Milton Berlinger
Milton Berlinger, better known by his stage name Milton Berle, was a pioneering American comedian and actor who became one of television’s first major stars.
-
C.
Harold G. Kiner
Harold G. Kiner was a United States Army soldier and Medal of Honor recipient who was killed in action during World War II.
-
D.
Walter Sillers
Walter Sillers was a prominent Mississippi political figure whose influence and legacy in the state led to major public buildings being named in his honor.
-
E.
Robert L. Lippert
Robert L. Lippert was an American film producer and distributor known for his prolific output of low-budget genre movies from the 1940s through the 1960s.
- 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1ff6b91a48190a04648d4cad2c4b1 |
completed | April 17, 2026, 9:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffeba1e4c08190a90f5102e0038056 |
completed | May 10, 2026, 2:21 a.m. |
Created at: April 10, 2026, 5 a.m.