Triple
T6480039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runaway with Del Shannon |
E146168
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Harry Balk |
E596406
|
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: Harry Balk | Statement: [Runaway with Del Shannon, producer, Harry Balk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harry Balk Context triple: [Runaway with Del Shannon, producer, Harry Balk]
-
A.
Harry Balk
chosen
Harry Balk was an American record producer and music executive known for his influential work in pop and soul music during the 1960s and 1970s.
-
B.
Arthur Seid
Arthur Seid is a film editor known for his work on the classic 1948 crime drama "Force of Evil."
-
C.
Donald Oenslager
Donald Oenslager was an influential American theatrical set designer and educator known for helping shape modern stage design on Broadway in the mid-20th century.
-
D.
Fritz Lanman
Fritz Lanman is an American technology executive and investor known for his leadership roles at companies like ClassPass and his early investment in and involvement with startups such as Square.
-
E.
Thomas Del Ruth
Thomas Del Ruth is an American cinematographer known for his work on acclaimed films and television series, including the coming-of-age drama "Stand by Me."
- 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_69c008fec7408190af7b146dc63d9750 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a4e764c819086828bb841f588e0 |
completed | March 22, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c65fd4fd408190ac7505e5b562cd73 |
completed | March 27, 2026, 10:45 a.m. |
Created at: March 22, 2026, 4:51 p.m.