Triple
T12208299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thirteen WNET New York |
E290890
|
entity |
| Predicate | analogChannelType |
P45106
|
FINISHED |
| Object | former VHF analog television |
—
|
LITERAL 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: former VHF analog television | Statement: [Thirteen WNET New York, analogChannelType, former VHF analog television]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: analogChannelType Context triple: [Thirteen WNET New York, analogChannelType, former VHF analog television]
-
A.
analogChannel
Indicates a relationship where a channel carries or transmits signals in analog (continuously varying) form rather than digital form.
-
B.
formerAnalogChannel
chosen
Indicates that an entity was previously an analog channel but no longer holds that status.
-
C.
isAnalogOrDigital
Indicates whether something operates using analog signals/representation or digital signals/representation.
-
D.
hasAnalogInputChannels
Indicates that an entity is equipped with one or more channels capable of receiving analog input signals.
-
E.
analogChannelHistoric
Indicates a relationship where an analog channel is associated with its historical or past states, readings, or configurations over time.
- 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_69d6ab65923081909acfc61b7a612233 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d920e312708190b4aede2e21f5f697 |
completed | April 10, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69d91c3d669c81908eea7ad61122d275 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:51 p.m.