Triple
T19872856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Let It Go |
E477562
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | David Spradley |
—
|
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: David Spradley | Statement: [Let It Go, writer, David Spradley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Spradley Context triple: [Let It Go, writer, David Spradley]
-
A.
David Spradley
chosen
David Spradley is an American songwriter and producer best known for his work in R&B and funk music, including contributions to hit songs like "So Many Tears."
-
B.
John Eisendrath
John Eisendrath is a television writer and producer best known for his work on series such as "The Blacklist" and "Alias."
-
C.
Craig A. Stough
Craig A. Stough is an American local government leader who serves as the mayor of Sylvania, Ohio.
-
D.
Scott Lobdell
Scott Lobdell is an American comic book writer best known for his influential 1990s run on Marvel's X-Men titles and for co-creating several prominent mutant characters.
-
E.
David Stavens
David Stavens is an entrepreneur and computer scientist best known as a co-founder of the online education platform Udacity.
- 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658d92f9c8190b363587ed1881c2c |
completed | April 20, 2026, 4:48 p.m. |
Created at: April 10, 2026, 1:51 p.m.