Triple
T9722637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Howard Sibshaw |
E235514
|
entity |
| Predicate | targetAudiencePerception |
P39479
|
FINISHED |
| Object | lovable rogue |
—
|
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: lovable rogue | Statement: [Howard Sibshaw, targetAudiencePerception, lovable rogue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetAudiencePerception Context triple: [Howard Sibshaw, targetAudiencePerception, lovable rogue]
-
A.
influencedPerceptionOf
Indicates that one entity has affected, shaped, or altered how another entity is perceived or understood.
-
B.
targetMarket
Indicates the group of consumers or organizations that a product, service, or campaign is specifically intended and designed to reach.
-
C.
typicalAudience
Indicates the group of people for whom something (such as a work, product, or resource) is primarily intended or most suitable.
-
D.
hasPublicPerception
chosen
Indicates that an entity is associated with a particular way it is viewed, judged, or regarded by the general public or society.
-
E.
relatesToAudience
Indicates a general relationship or relevance between something and a particular audience or group of recipients.
- 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_69ca84d0123c819096f9dc3b6abb0881 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9e75abd48190a6e6679ec51496e8 |
completed | April 1, 2026, 10:38 p.m. |
| PD | Predicate disambiguation | batch_69cd03c6ffc88190a5e9569e19122ad5 |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:20 p.m.