Triple
T9529570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pop |
E229850
|
entity |
| Predicate | formerlyFocusedOn |
P35083
|
FINISHED |
| Object | television listings |
—
|
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: television listings | Statement: [Pop, formerlyFocusedOn, television listings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerlyFocusedOn Context triple: [Pop, formerlyFocusedOn, television listings]
-
A.
formerFocus
chosen
Indicates that an entity previously served as the primary focus or main subject of attention, but no longer holds that status.
-
B.
canonicalFocus
Indicates that one entity is the primary or most representative focus or point of attention in relation to another entity.
-
C.
focusesOn
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
D.
focusOf
Indicates that one entity is the primary subject, target, or center of attention, activity, or interest for another entity.
-
E.
successorFocus
Indicates that one entity becomes the primary or main focus immediately after another entity in a sequence or process.
- 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_69ca8479934c81908006d0e6e970ae05 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98b1b93481909812245ac14e4988 |
completed | April 1, 2026, 10:14 p.m. |
| PD | Predicate disambiguation | batch_69cca56c44f88190a54a5d2a133bb07e |
completed | April 1, 2026, 4:56 a.m. |
Created at: March 30, 2026, 8 p.m.