Triple
T32310321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Civic TV Channel 83 |
E825480
|
entity |
| Predicate | timeSlotSpecialty |
P56910
|
FINISHED |
| Object | late-night programming |
—
|
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: late-night programming | Statement: [Civic TV Channel 83, timeSlotSpecialty, late-night programming]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeSlotSpecialty Context triple: [Civic TV Channel 83, timeSlotSpecialty, late-night programming]
-
A.
hasSpecialty
Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
-
B.
timeSlotOfWorks
chosen
Indicates the specific time period or interval during which the works (e.g., tasks, events, or activities) are scheduled or take place.
-
C.
isConsideredSpecialtyOf
Indicates that one field, practice, or area of expertise is regarded as a specialized branch or subset of another broader field.
-
D.
daySpecialization
Indicates a relationship where something is specifically tailored, assigned, or specialized for a particular day.
-
E.
openingSpecialty
Indicates the specific area of focus, expertise, or type associated with an opening (such as a job, position, or opportunity).
- 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_69f3491213b88190a57094d8697a7455 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c8159edc8190b1c87015e0c820e8 |
completed | May 3, 2026, 3:59 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f42fbc8190a06eb1044c9e6094 |
completed | May 3, 2026, 3:41 a.m. |
Created at: May 1, 2026, 12:46 a.m.