Triple
T22189695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | "Bye, Felicia" |
E548383
|
entity |
| Predicate | typicalUsageTarget |
P132779
|
FINISHED |
| Object | annoying person |
—
|
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: annoying person | Statement: ["Bye, Felicia", typicalUsageTarget, annoying person]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalUsageTarget Context triple: ["Bye, Felicia", typicalUsageTarget, annoying person]
-
A.
typicalTargetType
chosen
Indicates the usual or most common type or category of entity that serves as the target or recipient in a given relationship or action.
-
B.
usesTarget
Indicates that one entity employs, applies, or operates on another entity as its target or object of action.
-
C.
usageType
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
D.
typicalUsageFormat
Indicates the usual or standard way in which something is expressed, presented, or formatted in practice.
-
E.
targetsUseCase
Indicates that one entity is aimed at or designed to address a particular use case associated with another entity.
- 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_69e11e3e0c7c8190b30d278845e2497e |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12aac07d88190848c940863c0a0c7 |
completed | April 28, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69e71b48576c8190a8e93738fd9cfda5 |
completed | April 21, 2026, 6:38 a.m. |
Created at: April 16, 2026, 8:35 p.m.