Triple
T28564291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sports Radio 101.9 FM and 66 AM |
E722630
|
entity |
| Predicate | cityOfLicenseAM |
P4443
|
FINISHED |
| Object | New York, New York |
—
|
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: New York, New York | Statement: [Sports Radio 101.9 FM and 66 AM, cityOfLicenseAM, New York, New York]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityOfLicenseAM Context triple: [Sports Radio 101.9 FM and 66 AM, cityOfLicenseAM, New York, New York]
-
A.
cityOfLicense
chosen
Indicates the city in which an entity (typically a broadcast station or similar regulated service) is officially licensed or authorized to operate.
-
B.
formerCityOfLicense
Indicates that an entity previously held, but no longer holds, the official city of license designation for another entity (typically a broadcast station).
-
C.
countryOfLicence
Indicates the country that has issued or granted a particular licence.
-
D.
stateOfLicense
Indicates the jurisdiction or state that has issued or governs the relevant license.
-
E.
typeOfLicense
Indicates the specific kind or category of license associated with an entity.
- F. None of above.
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_69f01a5f69d08190ad5c0d2167078dec |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f6645ba71c81908044ade6ab577018 |
completed | May 2, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69f663362c008190a22afed262f1e426 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 4:06 a.m.