Triple
T14517127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Better Now |
E340548
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Teddy Walton |
E861783
|
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: Teddy Walton | Statement: [Better Now, writer, Teddy Walton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Teddy Walton Context triple: [Better Now, writer, Teddy Walton]
-
A.
Teddy Walton
chosen
Teddy Walton is an American record producer known for his atmospheric, genre-blending hip-hop and R&B work with artists like Kendrick Lamar, Bryson Tiller, and A$AP Rocky.
-
B.
David Walton
David Walton is an American actor best known for his comedic roles in television series such as "Perfect Couples" and "About a Boy."
-
C.
Teddy Walker
Teddy Walker is the charismatic, fast-talking protagonist of the comedy film "Night School," whose return to earn his GED drives the movie’s central story.
-
D.
Teddy McSwiney
Teddy McSwiney is a kind-hearted, charming young man from the Australian novel and film "The Dressmaker," known for his close relationship with protagonist Tilly Dunnage and his tragic fate.
-
E.
Wallace Woods
Wallace Woods is a historic residential neighborhood in Covington, Kentucky, known for its early 20th-century architecture and tree-lined streets.
- 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_69d822d9c0408190b9a2b3643e58bb4d |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69de9a6f50208190b687b505f5cd1aa2 |
completed | April 14, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a49484081908fd2030d33727a6d |
completed | May 8, 2026, 5:53 a.m. |
Created at: April 10, 2026, 1:21 a.m.