Triple
T16147899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeff Hephner |
E391834
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Peppermint |
E189820
|
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: Peppermint | Statement: [Jeff Hephner, notableWork, Peppermint]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peppermint Context triple: [Jeff Hephner, notableWork, Peppermint]
-
A.
Peppermint
chosen
Peppermint is a 2018 American action thriller film starring Jennifer Garner as a vigilante seeking revenge for her family's murder.
-
B.
Peppermint
Peppermint is a sharp-tongued, tech-savvy ally and strategist who guides the protagonist in the rhythm-action game Hi-Fi Rush.
-
C.
Kent Menthol
Kent Menthol is a menthol-flavored variant of the Kent brand of cigarettes, offering a minty, cooling smoking experience.
-
D.
Doublemint
Doublemint is a popular Wrigley chewing gum brand known for its long-lasting mint flavor and iconic twin-themed advertising.
-
E.
Cinnamon
Cinnamon is Rajesh Koothrappali’s small Yorkshire Terrier dog from the TV sitcom "The Big Bang Theory," often treated by him as a beloved companion and surrogate child.
- 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_69d87f1c65e48190aa2b4c472e9bafc4 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21d9551e081908391061b092ff31b |
completed | April 17, 2026, 11:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff7a7dc3481909f933acd72d6feff |
completed | May 10, 2026, 3:12 a.m. |
Created at: April 10, 2026, 5:01 a.m.