Triple
T5053081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kim Carnes |
E113831
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object | Gene Cotton |
E170270
|
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: Gene Cotton | Statement: [Kim Carnes, associatedAct, Gene Cotton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gene Cotton Context triple: [Kim Carnes, associatedAct, Gene Cotton]
-
A.
Gene Cotton
chosen
Gene Cotton is an American soft rock singer-songwriter and guitarist best known for his 1970s and early 1980s chart hits and collaborations with artists like Kim Carnes.
-
B.
Gordon Heath
Gordon Heath was an American actor, singer, and director known for his work on stage and in film, as well as for his influential career in Europe, particularly in France.
-
C.
David Sills
David Sills was an American jurist and former mayor of Irvine, California, who later served as the presiding justice of the California Court of Appeal.
-
D.
Cal Henderson
Cal Henderson is a British software engineer and entrepreneur best known as the co-founder and CTO of the workplace communication platform Slack.
-
E.
Louis Partridge
Louis Partridge is a British actor best known for his role as Viscount Tewkesbury in the Netflix mystery film "Enola Holmes."
- 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_69bd443aa1f88190abb992d138f2cf42 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7428d7a88190b990aedae390acbe |
completed | March 20, 2026, 4:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bea486b394819082ea80694843b29e |
completed | March 21, 2026, 2 p.m. |
Created at: March 20, 2026, 1:38 p.m.