Triple
T37892602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christina Haack |
E945187
|
entity |
| Predicate | networkGenre |
P167908
|
FINISHED |
| Object | home and garden 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: home and garden television | Statement: [Christina Haack, networkGenre, home and garden television]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: networkGenre Context triple: [Christina Haack, networkGenre, home and garden television]
-
A.
networkGenreFocus
chosen
Indicates that a network primarily centers its content or programming around a particular genre.
-
B.
websiteGenre
Indicates the thematic category or type of content that a website is primarily associated with.
-
C.
tvGenre
Indicates the genre or category to which a television show or program belongs.
-
D.
targetGenre
Indicates the genre that something is specifically aimed at, categorized under, or intended to belong to.
-
E.
visualGenre
Indicates the visual or stylistic category to which something belongs, such as its artistic or cinematic genre.
- 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_69f76ef0e8708190987c7254ed8c7abe |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd166a488190b1bf9316b0790801 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:19 p.m.