Triple
T23425738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arby’s |
E560789
|
entity |
| Predicate | hasCompetitor |
P1375
|
FINISHED |
| Object | Jimmy John’s |
—
|
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: Jimmy John’s | Statement: [Arby’s, hasCompetitor, Jimmy John’s]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jimmy John’s Context triple: [Arby’s, hasCompetitor, Jimmy John’s]
-
A.
Jimmy John’s
chosen
Jimmy John’s is an American sandwich restaurant chain known for its fast service and customizable submarine sandwiches.
-
B.
Johnny’s
Johnny’s is a major Japanese talent agency best known for producing and managing many of Japan’s most popular male idol groups.
-
C.
Carl's Jr.
Carl's Jr. is an American fast-food restaurant chain known for its charbroiled burgers and often provocative advertising campaigns.
-
D.
Bob’s Big Boy
Bob’s Big Boy is an American restaurant chain best known for its iconic chubby boy mascot in checkered overalls and its classic diner-style burgers and shakes.
-
E.
Gino's Hamburgers
Gino's Hamburgers was a regional fast-food restaurant chain in the United States, best known for its hamburgers and association with former NFL star Gino Marchetti.
- 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_69e2454cb1108190ab21ada5411a7146 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a54951688190a3c5382971af3e41 |
completed | April 29, 2026, 6:29 a.m. |
Created at: April 17, 2026, 5:47 p.m.