Triple
T20418433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stupid Cupid |
E500776
|
entity |
| Predicate | lyricist |
P1360
|
FINISHED |
| Object | Howard Greenfield |
—
|
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: Howard Greenfield | Statement: [Stupid Cupid, lyricist, Howard Greenfield]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Howard Greenfield Context triple: [Stupid Cupid, lyricist, Howard Greenfield]
-
A.
Howard Greenfield
chosen
Howard Greenfield was an American lyricist best known for his prolific pop songwriting in the 1950s and 1960s, including many hits with composer Neil Sedaka.
-
B.
Howard Green
Howard Green was a Canadian politician who served as the country's Secretary of State for External Affairs in the mid-20th century.
-
C.
Phil Greenberg
Phil Greenberg is an immunologist and biotech entrepreneur known for pioneering work in cancer immunotherapy and co-founding Juno Therapeutics.
-
D.
Allan Greenberg
Allan Greenberg is an American architect renowned for reviving and advancing New Classical architecture through his traditionally inspired yet contemporary designs.
-
E.
Dan Greenburg
Dan Greenburg is an American author and humorist best known for his satirical books and children's series such as "The Zack Files."
- 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_69e0b4a935588190b9446a99b37ced44 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67a4686a48190a808c86aa916ad56 |
completed | April 20, 2026, 7:11 p.m. |
Created at: April 16, 2026, 11:30 a.m.