Triple
T17554237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WLUP-FM |
E427548
|
entity |
| Predicate | callSignMeaning |
P15135
|
FINISHED |
| Object | The Loop |
—
|
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: The Loop | Statement: [WLUP-FM, callSignMeaning, The Loop]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Loop Context triple: [WLUP-FM, callSignMeaning, The Loop]
-
A.
The Loop
The Loop is an American television sitcom that follows a young professional juggling his demanding corporate airline job with the chaotic antics of his friends and family in Chicago.
-
B.
The Loop
chosen
The Loop is a classic rock radio brand historically associated with Chicago’s influential WLUP-FM station.
-
C.
In the Loop
In the Loop is a 2009 British political satire film, spun off from the TV series "The Thick of It," that lampoons government spin and the lead-up to war.
-
D.
Loop (Chicago)
Loop (Chicago) is the central downtown business district of Chicago, known for its dense concentration of offices, theaters, shopping, and its iconic elevated "L" train tracks.
-
E.
Downtown Reach
Downtown Reach is the central, urban section of the San Antonio River Walk known for its dense concentration of restaurants, shops, hotels, and cultural attractions.
- 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_69d889df6dc081908f67dbadc03c07ee |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e45620983c81909e71f938ce934efa |
completed | April 19, 2026, 4:12 a.m. |
Created at: April 10, 2026, 5:50 a.m.