Triple
T12278352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Primetime Emmy Award for Outstanding Guest Actress in a Comedy Series |
E292649
|
entity |
| Predicate | categoryDivision |
P87
|
FINISHED |
| Object | comedy |
—
|
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: comedy | Statement: [Primetime Emmy Award for Outstanding Guest Actress in a Comedy Series, categoryDivision, comedy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: categoryDivision Context triple: [Primetime Emmy Award for Outstanding Guest Actress in a Comedy Series, categoryDivision, comedy]
-
A.
categorySubdivision
Indicates that one category functions as a subdivision or subcategory within another broader category.
-
B.
category
chosen
Indicates that one entity is classified as a member or type within the grouping or class defined by another entity.
-
C.
featuredDivision
Indicates that one division is highlighted or given special prominence in relation to others within a particular context.
-
D.
canonicalDivision
Indicates that one entity is the standard or officially recognized subdivision or partition of another entity.
-
E.
catalogCategory
Indicates that an item or entity is assigned to, or belongs within, a specific catalog category.
- 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_69d6ab6856488190b5d31178d5015f8e |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d9261e1570819084bb4fdb44aa6aea |
completed | April 10, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69d91c4d9a9c8190aeb7beaf9792d8f0 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:52 p.m.