Triple
T17360818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duke Dumont |
E422060
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object | A*M*E |
—
|
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: A*M*E | Statement: [Duke Dumont, associatedAct, A*M*E]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: A*M*E Context triple: [Duke Dumont, associatedAct, A*M*E]
-
A.
A*M*E
chosen
A*M*E is a Sierra Leonean-born British singer and songwriter known for her work in pop and dance music, including collaborations with prominent electronic artists.
-
B.
Amm
Amm is an ancient South Arabian god, particularly revered in the Qataban kingdom as a principal deity associated with protection and tribal identity.
-
C.
AMA
AMA is the three-letter IATA airport code for Rick Husband Amarillo International Airport in Amarillo, Texas.
-
D.
AMA
AMA is the commonly used abbreviation for Japan’s Antimonopoly Act, the core law regulating competition and prohibiting monopolistic practices in the country.
-
E.
AMA
AMA is the leading professional association and lobbying group representing physicians and medical students in the United States.
- 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_69d889d520008190a26917a95bf1c2ea |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a4cacd881909fd722068b019f25 |
completed | April 19, 2026, 2:13 a.m. |
Created at: April 10, 2026, 5:44 a.m.