Triple
T23425737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arby’s |
E560789
|
entity |
| Predicate | hasCompetitor |
P1375
|
FINISHED |
| Object | Subway |
—
|
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: Subway | Statement: [Arby’s, hasCompetitor, Subway]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Subway Context triple: [Arby’s, hasCompetitor, Subway]
-
A.
Subway
Subway is a 1985 French crime-comedy film directed by Luc Besson, known for its stylish depiction of Paris’s underground subculture and featuring Isabelle Adjani and Christopher Lambert.
-
B.
Subway
chosen
Subway is a global fast-food restaurant franchise best known for its made-to-order submarine sandwiches and salads.
-
C.
IND Subway
IND Subway is the city-owned Independent Subway System in New York City, built in the early 20th century to compete with private transit operators and now forming a core part of the modern NYC Subway.
-
D.
Subway Wind
"Subway Wind" is a poem by Claude McKay that vividly captures the gritty, restless atmosphere of New York City’s underground transit system.
-
E.
Subway Stories
Subway Stories is a 1997 HBO anthology film composed of short vignettes set in the New York City subway, exploring the intersecting lives and experiences of diverse passengers.
- 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.