Triple
T19952374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Studs Terkel |
E479591
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | WFMT |
—
|
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: WFMT | Statement: [Studs Terkel, employer, WFMT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WFMT Context triple: [Studs Terkel, employer, WFMT]
-
A.
WFMT
chosen
WFMT is a Chicago-based classical music and fine arts radio station known for broadcasting live performances and cultural programming.
-
B.
WBEZ Chicago
WBEZ Chicago is a public radio station and media organization based in Chicago, best known as a major NPR member station and producer of influential podcasts and programs such as "This American Life."
-
C.
WQXR
WQXR is a New York City-based classical music radio station known for its curated performances, broadcasts, and cultural programming.
-
D.
WLS-FM
WLS-FM is a Chicago-based commercial radio station known for its classic hits format and shared heritage with the historic WLS brand.
-
E.
WBBM (AM)
WBBM (AM) is a major Chicago-based all-news radio station owned by Audacy, known for its continuous local and national news coverage.
- 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_69d8e522a17c819095165d4d24939fd8 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65a6c87388190a1bada3117acaf7b |
completed | April 20, 2026, 4:55 p.m. |
Created at: April 10, 2026, 1:54 p.m.