Triple
T20472547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Without Limits |
E502227
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | Randy Miller |
—
|
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: Randy Miller | Statement: [Without Limits, musicBy, Randy Miller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Randy Miller Context triple: [Without Limits, musicBy, Randy Miller]
-
A.
Randy Miller
chosen
Randy Miller is a film composer best known for scoring movies such as the long-distance running drama "Without Limits."
-
B.
Randy Mueller
Randy Mueller is an American football executive known for serving as a general manager for multiple professional teams, including in the NFL and the Alliance of American Football.
-
C.
Ray Miller
Ray Miller is an actor known for his role in the film "Crashing Towers."
-
D.
Randy Turpin
Randy Turpin was a British middleweight boxing champion best known for his stunning 1951 upset victory over Sugar Ray Robinson.
-
E.
Randy Waldrum
Randy Waldrum is an American soccer coach best known for his long tenure leading the Notre Dame women’s team to multiple NCAA titles and for managing both professional clubs and national women’s teams.
- 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_69e0b4ae5f1081908768b0c9a3a0bf38 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69962d810819091bb13fe73250e24 |
completed | April 20, 2026, 9:23 p.m. |
Created at: April 16, 2026, 11:33 a.m.