Triple
T20448898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flirting |
E501593
|
entity |
| Predicate | hasPositiveReception |
P103613
|
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: [Flirting, hasPositiveReception, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPositiveReception Context triple: [Flirting, hasPositiveReception, yes]
-
A.
notableReception
Indicates that something has received significant attention, recognition, or response from audiences, critics, or the public.
-
B.
hasReceivedCriticalAcclaim
chosen
Indicates that the subject has been widely praised or positively recognized by critics or expert reviewers.
-
C.
marketReception
Indicates how a product, service, or work is received, evaluated, and responded to by the market or audience after its introduction.
-
D.
hasCulturalReception
Indicates that an entity has been received, interpreted, or responded to within a particular cultural context or by a specific audience.
-
E.
portrayalReception
Indicates how a particular portrayal of someone or something is received, evaluated, or responded to by an audience or observers.
- 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_69e0b4ac0a1c81908845d0f8a56abce8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e68cfffae4819086c727f4143c2737 |
completed | April 20, 2026, 8:30 p.m. |
| PD | Predicate disambiguation | batch_69e57679eb40819086142df3e39c928e |
completed | April 20, 2026, 12:42 a.m. |
Created at: April 16, 2026, 11:32 a.m.