Triple
T8079910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DZAQ-TV |
E188587
|
entity |
| Predicate | analogChannel |
P80377
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [DZAQ-TV, analogChannel, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: analogChannel Context triple: [DZAQ-TV, analogChannel, 3]
-
A.
formerAnalogChannel
Indicates that an entity was previously an analog channel but no longer holds that status.
-
B.
hasAnalogInputChannels
Indicates that an entity is equipped with one or more channels capable of receiving analog input signals.
-
C.
analogChannelHistoric
Indicates a relationship where an analog channel is associated with its historical or past states, readings, or configurations over time.
-
D.
isAnalogOrDigital
Indicates whether something operates using analog signals/representation or digital signals/representation.
-
E.
usedAsAnalogFor
Indicates that one entity is employed as a comparison or illustrative counterpart to help explain, represent, or understand another entity.
- F. None of above. chosen
Provenance (4 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_69ca82b662e88190b9323daab8c28a21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb40a3f01c819096a2c9d5d5199fe6 |
completed | March 31, 2026, 3:33 a.m. |
| PD | Predicate disambiguation | batch_69cb049f1614819087360d1a4c6f0faa |
completed | March 30, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69cb14be17208190bb51c3dfcb613f20 |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 5:28 p.m.