Triple
T6435538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The G. Gordon Liddy Show |
E129884
|
entity |
| Predicate | hasCallInSegment |
P39559
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [The G. Gordon Liddy Show, hasCallInSegment, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCallInSegment Context triple: [The G. Gordon Liddy Show, hasCallInSegment, yes]
-
A.
hasLiveCallInSegments
chosen
Indicates that an event, program, or broadcast includes segments where participants can call in live during the session.
-
B.
hasSegmentOn
Indicates that one entity includes or occupies a specific segment or portion on another entity (such as a line, path, or sequence).
-
C.
hasCallInNumber
Indicates that an entity has an associated telephone number designated for receiving incoming calls.
-
D.
hasCodeIn
Indicates that one entity is represented, defined, or implemented within the codebase or coding context of another entity.
-
E.
hasCalledProgram
Indicates that one program has invoked or executed another program.
- 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_69c0084caac48190a7bc2ad8ba44536f |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c069415c3c8190b91bd12ae79edd26 |
completed | March 22, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69c060f96980819091bab9335922a457 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:45 p.m.