Triple
T13612741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No Name |
E325233
|
entity |
| Predicate | soldAt |
P15059
|
FINISHED |
| Object | No Frills |
E1051123
|
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: No Frills | Statement: [No Name, soldAt, No Frills]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: No Frills Context triple: [No Name, soldAt, No Frills]
-
A.
No Frills
chosen
No Frills is a Canadian discount supermarket chain known for its low prices, limited frills shopping experience, and sale of private-label brands like President's Choice.
-
B.
Strip No More
Strip No More is a song best known as a notable work by Danish songwriter and producer Morten Ristorp.
-
C.
Five Per Cent for Nothing
Five Per Cent for Nothing is a brief, jazz-influenced instrumental piece by the progressive rock band Yes, featured on their 1971 album Fragile.
-
D.
Off & Out
Off & Out is a musical project associated with producer and artist Last Last.
-
E.
Loosies
Loosies is a 2012 romantic dramedy film about a New York City pickpocket whose life is upended when a one-night stand reappears claiming he is the father of her unborn 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb0abe1208190a1e0a32dc141d836 |
completed | April 12, 2026, 2:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f78ae56e2081909c0fd044ce3730a9 |
completed | May 3, 2026, 5:50 p.m. |
Created at: April 9, 2026, 9:50 p.m.